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IDP Use Case: Transforming Restoration Practices

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Earthquakes, hurricanes, mudslides, electrical fires, and burst pipes are some of the natural incidences that are usually unforeseen. Buildings that are often at the receiving end during catastrophic calamities require immense repair work. Any comprehensive structure will, in this respect, indeed call for disaster recovery management, especially if it is a house or a company. It has scaled tremendously to be vital software in the construction industry, but it is notably critical in the catastrophe repair industry, where most companies are small. Table of Contents: But as structures progress, many organizations like yours struggle to cope with change. Often, the driving force of success is in the technology that forms the basis of these organizations. Let us think of the building and restoration industry and see what we come up with. These companies have to estimate all possible costs for a building construction project, including additional costs such as salary for office employees, wear and tear of equipment, office rent and other overhead expenses, and cost of all the materials used and wages to workers. Enhancing Data Management in Restoration Processes Intelligent Document Processing (IDP) tools can capture information from any format that has not been pre-formatted, including images and handwritten writings. This can be of great importance, especially in restoration processes where data could be in large quantities, in the form of field notes and sketches, among other things. The Importance of Accurate Costs and Expenses Some of the factors one needs to understand well to accurately estimate the cost of the project include the building material costs, the requirements, the procedures, and the codes that are to be followed, as well as the need to understand the market trends in terms of pricing. Such information may be found by analyzing a bid package and working through the contingencies and profit inherent in a bid or a given project. Two Significant Challenges: Documentation obstacles: One of the challenges associated with restoration events is collecting all the relevant and non-concocted paperwork. Some of the effects of this cumbersome procedure include the failure to complete some forms or the delay in completing them. Accounts Receivable Delays are attributed primarily to fourteen struggles stemming from a high turnover rate in accounting: payment cycles take longer. This not only impacts cash flow but also definitely causes a lot of headaches for the business’s dealings with its customers. The Impact of Intelligent Document Processing (IDP) Software on Restoration Businesses: Implementing Intelligent Document Processing (IDP) Several Challenges. Here are some of the key ones: Case Study Use case for restoration: The repair company wishes to provide the customer with an overview of line-item estimates for the job. Cost estimates should not be utilized as a list of negotiable items. Supplemental costs may apply if more damage or repair that has not been found or is hidden below present finishes is required. This also enables the client to correct himself or herself if they chose compositions that are not within the estimate or if they need extra work. This is because, in the course of the project implementation, changes will be made to adjust for the revised estimate and present it to the client. Any changes made to these documents will be recorded in a change order and presented to the customer for revision. System: It is a form of advanced digital document processing with natural language processing, multimedia processes, and feature extraction. Primary actor: Accountant/bookkeeper/Customer Scenario: To meet the customer’s request to extract the estimated line-item information from the final amount, the following processes should be considered: They ask for the extracted data to be formatted differently than the original document’s formatting. They clearly explain what should be ignored and what needs to be extracted. There are a total of 11 headers in the PDF; each row value contains three different pieces of information: one is the labor, the second is the material, and the third is the equipment information. They need to extract the labor and material information. For example, the following are the instructions for the needed to be extracted data and how it should look like output: Tabular output with headers and the order they should be in JSON form: ·”ITEM#”, mapped from the label in Yellow (as in the picture above) ·”ROOM”, mapped from the label in dark green (as in the picture above) ·”UNIT”, mapped from the label in Red (as in the picture above) ·”QTY”, mapped from the label in light blue (as in the picture above) ·”UNIT PRICE”, mapped from the label in light green (as in the picture above) ·”TOTAL” mapped from the label in pink/magenta (as in the picture above) However, we still need to extract and differentiate data for Labor and Material information. While mapping the extracted data to the new headers, as requested by the customer. As complicated as it looks and sounds, Algodocs can do exactly this request easily.  How to Use Algodocs to Extract We only need a sample file uploaded to Algodocs to create the extractor. There are many ways to upload a sample document. The user can automate importing files to Algodocs uploading from their device, business email, Gmail, or other cloud storage. Once the documents are uploaded, the system will extract data from your documents using Algodocs’ advanced AI engine without relying on templates or even labeling and training your files.  The results are the actual contents extracted from the sample document according to the rules you specify. We have Rule-based extraction and artificial intelligence mining, which can be integrated to synthesize both extraction methods. This can help you further improve your extracted data by putting it into the correct form and structure.  The system makes it easy to control extracted data from your documents and handle business exceptions. It allows you to export the extracted data directly to an Excel Spreadsheet or, with the integration of Zapier, automate exporting extracted data directly to your email, Google Sheets, or other cloud storage. Example of Output in Excel Key Takeaways This should explain how Algodocs has boosted the restoration business and its experience with the solution to prove that technology can transform any business. Let your team be an example of how adopting effective and progressive concepts can

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How Algodocs enhances bill of lading processing

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A bill of lading, shortened as BL or BoL, is a legal document given by a carrier (a company that provides transportation) to the shipper. It outlines the particulars of the goods being transported, including the kind, quantity, and destination of the goods. In addition, a bill of lading functions as a shipping receipt when the carrier finalizes the delivery of the goods after a given destination. This document must accompany the shipped products, no matter the form of transportation, and must be signed by an authorized representative from the carrier, shipper, and receiver. Contents • INTRODUCTION• WHAT IS THE PURPOSE OF A BILL OF LADING?• WHAT IS IN A BILL OF LADING?• DIFFERENT TYPES OF BILLS OF LADING.• CHALLENGES WITH MANUAL PROCESSING:• IMPLEMENTING INTELLIGENT DOCUMENT PROCESSING (IDP)• BENEFITS OF INTELLIGENT DOCUMENT PROCESSING (IDP):• CASE STUDY• KEY TAKEAWAYS What Is the Purpose of a Bill of Lading? A bill of lading has three primary purposes. First, it is a document of title to the goods described in the bill of lading. Second, it is a receipt for the shipped products. Finally, it represents the agreed terms and conditions for the transportation and eventual release of the shipped goods. What Is in A Bill of Lading? Typically, a bill of lading will include the names and addresses of the shipper (consignor) and the receiver (consignee), shipment date, quantity, exact weight, value, and freight classification. Also included is a complete description of the items, including whether they are classified as hazardous, the type of packaging used, any specific instructions for the carrier, and any special-order tracking numbers. Why Is a Bill of Lading Important? A bill of lading is a legally binding document. The carrier and the shipper are given all the essential details to help them process a shipment correctly. Hence, it can be used in litigation if the situation requires it. The parties to it will be highly knowledgeable about the document as required by the law to ensure that there is no compromise in the safety and security of your goods. A bill of lading is undisputed proof of shipment. Furthermore, it allows for segregating duties, a vital part of a firm’s internal control structure, to prevent theft. Different Types of Bills of Lading Some of the most common include: Challenges With Manual Processing Some of the known challenges are: Implementing Intelligent Document Processing (IDP) Much of the information needed to execute logistics and supply chain operations is manually extracted from data sources such as the Bill of Lading. Automating the processing of instructions for the Bill of Lading proves to be crucial in increasing back-office productivity and, consequently, improving customer service performance. If traditionally conducting these activities by manually copying and pasting data carries the risk of errors and is an obstacle to maximizing operational efficiency, the value of automation must be highlighted. Benefits Of Intelligent Document Processing (IDP) CASE STUDY Imagine XYZ company, which is a logistics firm. It receives the shipment. The manager determines the type and amount of goods that need to be ordered. They then fill out a purchase order (PO), and XYZ’s owner reviews and initials each PO before it is emailed to the vendor. The vendor gathers the orders and signs a bill of lading along with a representative from the overnight carrier. The forwarder then supplies products to the ship and provides the invoice to the manager, who compares the bill of lading details with what was mentioned on the PO. If the information matches, the PO and the bill of lading are sent to the owner, who reviews the documents and writes a check payable to the vendor. Fields That Can Be Extracted: Example of extract data output: Enhancing Accuracy with Automated Data Extraction Algodocs can extract data automatically from the Bills of Lading. This step dramatically improves efficiency and offers new prospects for success in logistics. Applying Algodocs to the Bill of Lading allows the necessary data to be automatically extracted from the PDFs and images of the handwritten document received from the carrier and a new document structure from the Bill of Lading to be created quickly, eliminating the need for repetitive and error-prone manual work. Improving Efficiency with Algodocs AI Algorithms Bill of Lading instructions are often accompanied by various documents in different formats, as each company chooses the format best suited to its needs when sending instructions to the carrier. Algodocs represents a breakthrough in managing Bill of Lading data extraction because Algodocs AI algorithms process text recognition; this process not only speeds up processing but also minimizes the possibility of errors. KEY TAKEAWAYS Algodocs is a potent system that combines OCR, NLP, and ML technologies to provide a tool capable of extracting data from heterogeneous documents. It is particularly useful in creating a Bill of Lading. With Algodocs, you can automatically extract any field from bill of lading (BOL) documents. It can also extract critical data from Bill of Lading Documents. Do not waste time on manual extraction or building complicated templates. The Algodocs automated extractor (pre-trained model) recognizes Bill of Lading document fields that are out of the box and is flexible enough to adapt as documents evolve. Final Thoughts Algodocs proves to be the ideal solution to the challenges of bill-of-lading document processing. It uses new Artificial Intelligence and on-demand data processing to recognize any document, irrespective of the text, with complete quality assurance. The AI extractor in Algodocs not only reduces errors in data extraction but also allows businesses to: Documents Algo Docs AI-driven document processing became possible thanks to a variety of our services, built on top of a general AI platform for processing unstructured data. Contact us for more details and get a head start on this journey to enhance your operations. Follow this link to Schedule a Demo and Sign Up.

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How to Extract Handwritten Data from PDFs with Algodocs?

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Table of Contents Want to learn how to extract handwritten data from PDFs easily for your business documents? Algodocs is a powerful AI platform developed based on the latest technologies to streamline your processes and free your team from annoying and error-prone manual data entry by offering fast, secure, and accurate document data extraction. It helps you get rid of your workforce from repetitive, time-consuming, and error-prone manual data entry tasks such as extracting handwritten data. With its AI capabilities, Algodocs gives one of, if not the best, user experiences and interfaces. Areas and applications of Algodocs include extracting handwriting, tables, key-value pairs, marks, and signatures from PDFs and image files. Algodocs offers a forever free subscription, with 50 pages processed every month. What is OCR? Optical Character Recognition (OCR) engines are primarily focused on machine-printed text and may produce low accuracy for handwritten text. Intelligent Character Recognition (ICR) is an advanced recognition system that is used to recognize handwritten text. This allows the automatic conversion of text in an image into letter codes that are usable within computer and text-processing applications. Although many processes involve computer-based operations and are implemented in a digital environment, paper is still widely used across most core business processes such as mortgage origination, order fulfillment, contracts, and other documents that usually require handwritten input and signatures. Nowadays, the digitalization of paper documents plays an important role, and deciding on the right data capture software is critical since handwriting recognition, unlike printed text recognition is a more complex task that usually involves advanced deep learning algorithms. How Does Algodocs Do It? Handwritten data extraction from PDFs is implemented by converting handwritten text into machine-printed text with high accuracy. With the Intelligent Character Recognition (ICR) of Algodocs, you can automate your document processing workflow and get rid of manual data entry. Scan your paper documents with handwritten text and let Algodocs automatically extract data and convert it to Excel or JSON. Let’s consider the following portion of a scanned document, which contains a table of five columns filled with handwritten numbers. If you upload this image to your account at Algodocs, you will see the following output, which has 100% accuracy. Algodocs uses advanced ICR engines trained with Artificial Intelligence algorithms and Deep Learning. Extracting data from various document formats could be a challenging task, especially when it comes to the necessity to extract specific data sets from files containing different types of documents that span across multiple pages. In these quick materials, we will list key features that are available in Algodocs, and which will help you to extract data from your documents using the Algodocs advanced AI engine without relying on templates or even labeling and training your files. What Are the Supported File Formats for Data Extraction? You may upload to Algodocs different types of files of different Image formats for data recognition and data extraction: What Are the Supported Languages for Data Recognition? Algodocs supports data extraction from documents with Arabic, Armenian, Belorussian, Bulgarian, Catalan, Chinese, Croatian, Czech, Danish, Dutch, English, Estonian, Filipino, Finnish, French, German, Greek, Hebrew, Hindi, Icelandic, Indonesian, Italian, Japanese, Korean, Lao, Latvian, Lithuanian, Macedonian, Nepali, Norwegian, Persian, Polish, Portuguese, Russian, Serbian, Slovak, Slovenian, Spanish, Swedish, Telugu, Thai, Turkish, Ukrainian, Vietnamese, and many other up to 200 languages. How to Extract Handwritten Data from PDFs Using Algodocs Step 1: Log in to your Algodocs account and go to the home page which is the Dashboard. Step 2: Click on the Extractors tab, where you can see the Create button on the top right side, click on it. Step 3: Choose the Custom Extractor, for getting structured data from your documents as you need it. Step 4: A pop-up window will appear, upload your sample file to extract data from. Click on the Choose file, to locate the document from your device storage folder, then assign a name to the extractor. Once done, click on the Create Extractor button. It will populate under Extractors as below; in this article, our example is called “Sample1.” Step 5: Click on the blue button labeled “Manage”, to create the data to be extracted. Step 6: Click on Add to choose what type of extraction method you want, here, you may use rule-based and AI extraction. In this example, we will choose the AI extraction method, “Form Data Extraction.” After clicking on “Form data extraction”, the page that you want to extract data from will appear on a new page. On the Top Right corner click on” Continue”. Step 7:  The raw data from your document is displayed. Now use available filters to select certain data, and update, or format the extracted data as you like. Once done, write the Field/Table name on the Left side inside the blank text box, and click the SAVE button on the right side. Step 8:  Now go to the extracted date and choose the extractor name, from the first drop-down menu. The extractor will populate the extracted date information. To view the extracted data, click on the Rows, and the data will populate as below.  Then choose to download the data as Excel, JSON, or XML Final Thoughts As we can see Algodocs performs well in handwritten text extraction from scanned documents. Feel free to start a free subscription right now and test your handwritten scanned documents. You can use Algodocs for free forever, and you will have 50 pages per month. If you need to process a higher number of pages, then please see our affordable pricing plans. Please contact us if you need any assistance.

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How to Convert Handwritten PDF to Text in 2024

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Digitization enables ease in handling documents to save, share, and access material. However, converting handwritten PDFs to text is still a big challenge. Old methods of digitization are not precise enough in the conversion of handwriting to editable and machine-printed text because they lead to errors and confusion. In the current era of advanced technology, many tools and techniques are very helpful to handle this challenge. The tools to convert handwritten PDFs to text use OCR technology and transform them into editable text within seconds. Such tools make it easier to organize and share your words in that document. To know how to convert scanned files with handwritten text, we will discuss free options that will simplify your conversion of handwritten PDFs. These tools also make digitization and data extraction more manageable. Challenges in Handwriting data extraction There are many challenges in handwriting data extraction due to several reasons. The process of handwriting data extraction includes digitization. It converts handwritten documents into that digital format. This step is easy and straightforward. The real and noteworthy challenges in handwriting data extraction arise when we have to turn these scanned images into editable text. Here we will see some valid challenges in the extraction of data from handwritten scanned images; 1. Irregularities in handwriting styles The primary challenge is the irregularities in handwriting styles. People generally write in many different ways. They use different angles, forms, and sizes of letters. These irregularities make text recognition a complicated process. In this case, machine learning algorithms are very useful to improve accuracy, but sometimes, they also struggle with chaotic or unreadable handwriting. 2.  Transcription The second most important challenge is transcription. It can also be problematic, especially when you are dealing with older documents where liquid ink is faded or scanned image paper has worsened. In these situations, the conversion of scanned PDF images into editable text can produce errors. These errors lead to inappropriate data extraction. 3.  Context The third important challenge is context. It plays a crucial role in precise data extraction. Sometimes, handwriting recognition systems misinterpret numbers or letters. They interpret wrongly, especially when there is high uncertainty or misplaced information. Addressing this challenge needs cutting-edge technology and advanced Machine Learning Algorithms. Such technologies ensure correct transcription and reliable Data extraction. What are the main methods or tools for Automated Handwriting data extraction? For automated handwriting data extraction, there are numerous primary techniques or tools available. However, a few noteworthy and useful ones are as follows: 1.    Optical Character Recognition The most common method for converting handwritten PDFs into editable text is Optical Character Recognition. It works by examining the scanned images of documents and identifying the shapes and patterns of individual characters. Optical Character Recognition tools can help in extracting text from native PDFs. However, its performance decreases when used for extracting handwritten. 2.    Intelligent Character Recognition The second most common method is Intelligent Character Recognition. It is considered for Handwriting recognition text. This Automated Handwriting data extraction method uses machine learning algorithms to understand several styles of handwriting. Intelligent Character Recognition is particularly convenient when you need to convert handwritten PDFs to text. The main reason behind this is that it can; Intelligent Character Recognition is far more flexible than in print fonts. 3.    Free Online Tools Many free online tools can help you convert handwritten PDFs to text. These online tools often use both OCR and ICR technologies for the conversion of PDF to text. Some prominent and helpful tools are; Users can upload their handwritten PDFs to these online services. These tools process the documents to extract text. The best part of these tools is that you can download the resulting editable text or copy it for further use. These free online tools offer a suitable way to convert handwritten PDFs to text. Algodocs, on the other hand, is an excellent choice if you’re searching for a more specialized tool that enables you to extract not just handwritten data but also any kind of data, including tables and structured data. Algodocs offers a forever free subscription, with 50 pages processed every month. Handwriting to Text: Easily Convert Handwriting to Text using Algodocs The best way to convert handwritten pdf to text is by using Algodocs. It is a convenient and amazing tool for converting handwriting to text online for free. It streamlines the process of digitization by providing an easy platform for usage. You can convert scanned handwritten documents and convert into editable text. Algodocs is equipped with advanced text recognition and machine learning algorithms. It guarantees high accuracy even with several handwriting styles. How to extract handwritten data using Algodocs Step 1: Log in to your Algodocs account and go to the home page, which is the Dashboard. Step 2: Click on the Extractors tab, where you can see the Create button on the top right side, and click on it. Step 3: Choose the custom extractor for getting structured data from your documents as you need it. Step 4: A pop-up window will come out, and this is where you upload your sample file to extract data from. Click on the Choose file to locate the document from your device storage folder, then assign a name to the extractor. Once done, click on the Create Extractor button. It will populate under Extractors as below; in this article, our example is called “Sample 1.” Step 5: Click on the blue button labeled “Manage”, to create the data to be extracted. Step 6: Click on Add to choose what type of extraction method you want. Here, you may use rule-based and AI-based extraction. In this example, we will choose the AI extraction method, “Form Data Extraction.” After clicking on “Form data extraction”, the uploaded page that want to extract data from will appear on a new page. Then, on the top right corner, click on ” Continue.” Step 7:  The raw data from your document is displayed. You can now use available filters to select certain data and update or format the extracted data as you like. Once done, write the Field/Table name on

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Data Extraction from PDFs: The Best Tool and Techniques

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PDFs are ubiquitous in every organization, serving as the go-to format for sharing and exchanging business data. However, extracting, editing, or parsing data from these files can be a lot of work to do. In today’s data-driven world, efficiently extracting information from PDF documents is essential. This article talks about the problems with getting data from PDFs and shows how to extract data from PDFs to Excel online. Whether you need to get text, and tables, or make PDFs searchable, we’ll cover solutions that are fast, accurate, and easy to use. Challenges in PDF Data Extraction: Let’s explore some of the key challenges encountered in PDF data extraction, shedding light on why what may seem like a simple task can often become quite complex. How to Extract Data from PDF Files in 2024: Extracting data from PDFs used to be a lot of work when the technology hadn’t advanced back in the days. However, now, with the advent of AI, OCR, and NLP, you don’t have to spend hours on manually extracting the data. All you need is an efficient tool like Algodocs that does the job for you accurately and easily. Let’s look at different PDF data extraction methods in 2024: Do it Manually While not the preferred method in 2024, manual data extraction remains a necessity for startups or beginners who are not ready to invest in good PDF data extraction software or are new to technology. Whether handling school documents, business reports, medical records, or any other file type, manual extraction is still widely utilized, although it is considered a less refined approach. Use Adobe Acrobat For more professional-grade PDF page extraction, Adobe Acrobat is a solid option. Although it’s not free, you can try it out with a 7-day free trial. Adobe Acrobat offers various plans, with Acrobat Pro starting at $19.99/month. This plan includes a range of features to streamline your document management process. Adobe Acrobat retains all interactive components of the PDF, including hyperlinks, comments, and forms. It allows you to extract any number of pages and save them as separate files or split the PDF into multiple PDFs, but all at a cost. You wouldn’t think it’s free, right? While Adobe Acrobat is a well-established tool for working with PDFs, it lacks the advanced data extraction capabilities of automated data extraction tools like Algodocs. Such a tool utilizes the latest technology to extract a wide range of information from PDFs and images, including handwriting, tables, and key-value pairs. This extracted data can then be exported into usable formats like CSV or Excel, making it ideal for integrating with accounting software or further analysis. In contrast, Adobe Acrobat offers limited data extraction functionalities. Automate Data Extraction with AI-powered OCR Technology What if you need to extract pages based on their content? Consider a scenario where you need to extract and analyze all invoices or pages containing specific key values such as names, dates, emails, total, address, etc. In such cases, an AI-powered OCR (Optical Character Recognition) tool can be invaluable. One important and powerful tool is Algodocs which we’re going to discuss in detail later in the article. It is the easiest way to get data from PDFs to Excel. Automated PDF Data Extraction: Algodocs Experience the power of Algodocs, an innovative AI data extraction platform designed to streamline your document processing workflow. With Algodocs, you can effortlessly extract valuable information from scanned files, including images, PDFs, Word, and Excel files. Whether these are HR forms, bank statements, purchase lists, or sales invoices, Algodocs handles them all with high accuracy. Gone are the days of manual data extraction. Algodocs empowers you to access and extract editable data effortlessly. Now get rid of the tedious tasks and say hello to editable formats like Excel, JSON, and XML, and seamless integrations with other software such as accounting or databases. Best of all, Algodocs offers a forever free subscription plan, allowing you to process up to 50 pages per month without any cost, so you can extract data from PDFs for free! Key Features of Algodocs PDF Extraction: Get Started in Minutes: The screencast video below shows how to quickly convert PDF files and photos into editable formats like Microsoft Word, Excel, PowerPoint, Text, or RTF. Moreover, a summary of the steps required for transforming a PDF into an editable Excel file is provided below. Convert PDF files and images into editable files in less than a minute. Step 1: Log in to your Algodocs account. Step 2: From the Dashboard, click on the File Manager tab  Step 3: Right-click on the root , and a drop-down menu will pop up showing available options such as Convert PDF/Image to Editable Files Step 4: Click on Convert PDF/Image to Editable Files . Step 5: Click on the blue button labeled + Choose files, which allows you to upload your file. Once you select the PDF or image, it will be uploaded. Step 6: Next, select the document language from the language drop-down menu. Feel free to select more than one language, if your file has multilanguage text. Step 7: Select the desired output file format, from the Output file type, drop-down menu. In this demonstration, we will select Excel. The other output types include MS Word, PowerPoint, Text, RTF, and HTML Step 8: The next step is to upload files by clicking on the Upload button , and the magic will start (Algodocs will process the file in no time). Step 9: Once the conversion is complete, the uploaded document will disappear from the pop-up window, and you can click on the Close buttonlocated at the bottom right corner to go back to the File Manager window. Step 10: Walla, an icon to access and download the converted Excel file is shown to the left of the file type icon. Step 11: As soon as you click on the Excel icon, the file will be downloaded. Figure 1. shows a sample PDF used for this demonstration, and Figure 2. shows the output Excel file. Figure 1. A sample PDF file was uploaded and processed by Algodocs. Figure 2. The Excel file produced by Algodocs that contains the content of the uploaded PDF. Highly accurate results

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What is a PDF Parser?

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A PDF Parser is a program or a library that enables end-users and organizations to parse data from native PDF documents. Often, organizations need to parse PDF documents for specific fields such as Account Number, Date, Address, Bill to/from information, or parse tabular data. PDF Parsers are usually needed and used for processing and parsing data from large amounts of documents. On the other hand, when you have a handful of documents you simply go and copy the data you need from PDF documents manually and paste it to Excel or anywhere you need it to be. PDF Parsers enable end-users to get data from hundreds and thousands of PDF documents in real time by saving huge amounts of time and, thus, money. Parsing pdf documents isn’t an easy task. There are various ways native pdf documents are generated and parsing data from such pdf documents requires smart approaches. Parsed data from PDF documents greatly varies depending on the industry, which means the data parsed might also greatly change, which complicates the task. Parsing PDF medical forms, which contain specific fields such as First, Middle, and Last names, Sex, Date of Birth, etc. are very different from PDF purchase orders that contain mainly the items in the tabular form with such columns as Item No, Code, Quantity, Item Price, Amount, etc. Therefore, if PDF Parser produces just a bunch of text from a PDF document it does not make much sense for the end-user. What end-users or organizations require is the structured data parsed from PDF documents. In other words, PDF Parser should extract from PDF documents only the data the end-user needs and in the right structured format. For this, the PDF Parser must be smart and flexible enough to parse PDF documents with various layouts and data types. How to parse PDF documents with various layouts? Algodocs allows you to parse PDF documents of any complexity in their layouts and type of data. With the flexible extracting rules of Algodocs, you can parse data from PDFs with different layouts. It is very easy and quick to set up extractors in Algodocs for your PDF documents. We provide 100% free technical support and are ready to set up extractors for you. While we provide free support for creating extracting rules, you may check our help and support section if you wish to learn how to create extracting rules in Algodocs. Watch the following introductory video to get an idea of how it works in Algodocs. Feel free to start a free subscription right now and parse your pdf documents. You can use Algodocs free forever with 50 pages per month. If you need to process a higher number of pages, then please see our affordable pricing plans. If you have specific requirements and need a custom solution, please contact us.

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Convert PDF to JSON – Convert PDF Documents to Structured JSON Objects

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Table of Contents Introduction Organizations in various industries widely use PDF documents, since no doubt PDF is a common document format for businesses to transfer data. Purchase orders, Invoices, Agreements, and many more document types are interchanged in PDF formats. On the other hand, JSON is another format that represents data in a structured format, which is widely used in transferring data between web applications. As a result, Working with JSON is much easier than with PDF. Therefore, in this article, we will talk about PDF and JSON formats and how you can convert your PDF documents to JSON format. What is a PDF? PDF (Portable Document Format) was initially developed by Adobe® Systems in 1992 and is standardized as ISO 32000. What makes PDF so popular is it is independent of the application software, hardware, and operating system. Other than text and images PDF files may contain a variety of content such as annotations, form fields, layers, etc. There are many advantages of PDF format such as multi-dimensionality, which we have already mentioned – being able to contain various types of content, text, images, videos, vector graphics, interactive fields, hyperlinks, and buttons. Moreover, PDF documents are easily created and viewed on different devices.  Security in PDF was one of the primary concerns of Adobe® Systems. Therefore, PDFs have different access levels to protect the content and the whole document, such as passwords, digital signatures, and watermarks. However, some of the downsides of a PDF are the complexity of editing and especially extracting data from it. Moreover, PDFs are not generated in the same way, so different PDF files can be created in various ways, which complicates the task of extracting data from PDF documents. What is a JSON? JSON (JavaScript Object Notation) is a very popular data format, which appeared in the early 2000s. JSON is a language-independent data format and is used to transfer data between software applications, particularly web applications, usually between server and client.  Most of the API integrations are realized using JSON format for data transfer since it is very easy to work with JSON. Consider a JSON object called person, which contains the following information:{   “name”: “John”,   “surname”: “Doe”,   “age”: 25} Accessing fields of a JSON object is as simple as using the name of the object and the field name you want to access by separating them with a dot as follows: To access a person’s name we use person.name, which will give us “John” as a result. Similarly, we do for surname and age fields: person.surname, person.age Note how easy it is to access any field of a JSON object, which is definitely not compared to accessing specific information in the PDF document. How does JSON differ from PDF? Although PDF and JSON are both widely spread and used, there is a huge difference between PDF and JSON. The difference between them is simply in the purpose of their usage. PDF is mainly used for exchanging information between humans, since it contains text, graphics, illustrations such as images and videos, etc. On the other hand, JSON is mainly used between computer programs and different applications for communicating and exchanging data between each other. It is not an easy task for a human to read information from a JSON file, especially if it is a compressed one, but it is a perfect way to access information from JSON for a software application. The opposite goes for the PDF. Therefore, PDF and JSON become important, useful, and helpful only when they are used in the right place and for the right purpose. How to Convert PDF to JSON? Often, organizations need to transfer data to other programs for further processing. This data is often stored in PDF documents since businesses often speak to each other in a “PDF language”. However, extracting information from PDF documents can be challenging.  The simplest solution is that you can always copy and paste text from a PDF and send it to where it belongs. However, this simple approach has many problems, since first of all this will work only with native PDF files (not scans) for which you can even use some free PDF Parsers. Another problem even if your PDF documents are all native, it is not easy to copy the entire table from a PDF by maintaining its format, especially if the table spans over multiple pages, for example, 100 or 1000 pages. Additionally, often organizations need to extract specific data from PDFs, for example not the entire table, but instead specific rows or columns based on some conditions. Last, but not least, it is not worth spending your valuable time on menial data entry! Convert PDF documents to JSON with Algodocs Algodocs offers a perfect solution to extract any type of data from PDF documents and transfer it to other programs in real-time. Algodocs can extract fields and tables of any complexity from native as well as scanned PDF documents. You can convert your PDF documents to JSON in three steps with Algodocs. Feel free to start a free subscription right now and convert your PDF documents to JSON. You can use Algodocs free forever with 50 pages per month. If you need to process a higher number of pages, then please see our affordable pricing plans.

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Extract handwritten text from scanned PDFs and images

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Optical Character Recognition (OCR) engines are primarily focused on machine-printed text and may produce low accuracy for handwritten text. Intelligent Character Recognition (ICR) is an advanced recognition system that is used to recognize handwritten text. This allows the automatic conversion of text in an image into letter codes that are usable within computer and text-processing applications. Although many processes involve computer-based operations and are implemented in a digital environment, paper is still vastly used across most core business processes such as mortgage origination, order fulfillment, contracts, and other documents that usually require handwritten input and signatures. Nowadays, the digitalization of paper documents plays an important role, and deciding on the right data capture software is critical since handwriting recognition unlike printed text recognition is a more complex task that usually involves advanced deep learning algorithms. Algodocs: Deep Learning Handwriting Recognizer Algodocs is capable of converting handwritten text into machine-printed text with high accuracy. With the ICR of Algodocs, you can automate your document processing workflow and get rid of manual data entry. Scan your paper documents with handwritten text and let Algodocs automatically extract data and convert it to Excel or JSON. Let’s consider the following portion of a scanned document, which contains a table of two columns filled with handwritten numbers. If you upload this image to your account at Algodocs, you will see the following output, which has 100% accuracy. Algodocs uses advanced ICR engines trained with Artificial Intelligence algorithms and Deep Learning. The above example includes mostly digits. Another example with characters is given below. The following is the extracted text by Algodocs from the above image. As we can see Algodocs performs well in handwritten text extraction from scanned documents. Feel free to start a free subscription right now and test your handwritten scanned documents. You can use Algodocs free forever with 50 pages per month. If you need to process a higher number of pages, then please see our affordable pricing plans. If you have specific requirements and need a custom solution, please contact us.

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A Guide on Extracting Tables From Low-Quality Scanned Documents

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Many companies deal with thousands of documents every month. Document workflow automation becomes vital for such companies as the number of documents increases. One of the most frequent and at the same time tedious operations when processing documents is reading data from tables, especially when documents are scanned PDFs or images. Automating table extraction from scanned documents and exporting them into Excel or JSON within seconds is a dream for every company dealing with manual data entry. Automating table data extraction from scanned documents and images reduces operational costs and saves a lot of time. In this article, we will talk about table extraction from scanned documents or images with low quality. You, most probably, came across some online tools that can extract tabular data from documents. However, there are a few that really work with low-quality scanned documents or images taken by a mobile device. Optical Character Recognition (OCR) is the technology used for converting scanned images into text. However, standard OCR tools require you to apply certain image processing operations on the images before you can apply OCR on them. Without manual pre-processing, OCR will fail in most cases, and accuracy will be low. Unfortunately, even with pre-processing operations free OCR tools produce poor performance. How to extract tables from scanned PDFs and images with low quality? Algodocs has an advanced AI-powered OCR engine that automatically handles any type of scanned PDF or image with a low quality. Algodocs accepts either colorful scanned images, black and white, or any other settings and extracts data with high accuracy. Algodocs can process scanned images with as low a dpi as 75. If you have scanned PDFs or images with low quality, then Algodocs is the right solution for you. You may start a free subscription right now and test your own scanned documents since we offer a free subscription (forever) with 50 pages per month. If you need to process a higher number of pages, then please see our affordable pricing plans. Please read our article on the basic steps for table extraction from documents here: Extract tables from PDF and scanned documents Algodocs: the best software tool to extract tables from scanned PDFs and images Consider the portions of the scanned documents below and the tables that Algodocs extracted from them. Example #1 Example #2 Extracted table by Algodocs As you can see, the accuracy of Algodocs is perfect even with low-quality scans. However, there are cases when scanned images may cause Algodocs to make mistakes concerning small characters such as punctuation or other symbols (points, commas, date separators, etc.). Let’s have a look at the example below with a scanned image and see what Algodocs could extract from it. The extracted table from the above-scanned image is shown below. As you can see, there are numbers that are extracted with wrong decimal separators (indicated in red circles), i.e. a decimal point is mistakenly recognized as a comma. This is due to the dark background that some rows have on the image. With the help of flexible extracting rules of Algodocs, the workaround is quick and simple. Whenever you have low-quality scanned PDFs of images, we always advise you to follow the steps explained below. Step1. Remove all points and commas from the numbers We apply the ‘Search & Replace’ filter in Algodocs by using regular expressions as the search type. We apply this rule to all the columns in the example below, but you can restrict this rule to a specific column when needed. In order to find all dots or commas we use \.|, as the search term and we leave empty the second field (replace by this), since we simply want to remove them. Step 2. Convert all numbers to their previous format Since we removed all points and commas from numbers, they actually increased, i.e. multiplied by 100 we can say (2,378.63 became 237863). Therefore, since we know that our numbers had 2 decimal places, we can divide all numbers by 100 to get the original numbers. The ‘Arithmetic Operation’ filter helps us implement exactly this. We divide numbers by 100 in the last column as shown in the example below. You may apply this filter to other columns too. That’s it. We got numbers in their original form with 100% accuracy! The same approach can be applied to other symbols when you have documents with a low quality. Please, contact us if you need any assistance.

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Extract Tables From PDF and Scanned Documents

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Extracting tables from PDF documents is always a tedious task, especially when the documents are scanned PDFs. Even when the documents are computer-generated PDFs, it can still be a complex and annoying task, since copying a tabular text from a PDF and pasting it to an Excel spreadsheet is not always as simple as it may look. Moreover, manual data entry with human interaction involves errors in addition to wasting time. How to convert PDF or scanned tables to Excel spreadsheets? There are free online tools that you can use to convert PDF tables to Excel spreadsheets if the PDF document is a text document (not scanned). Even for system-generated PDF documents, those tools just convert a table to Excel as is, without letting you filter a table and convert it into the format you need. Especially when tables span over multiple pages of a PDF, you definitely need to trim out all unnecessary text that occurs between pages, like footer and header information. Moreover, sometimes you might need to filter out either some rows or even columns of a table itself. Imagine table extraction from scanned documents! What if those scanned documents are of low quality? Alternatively, even worse, what if those documents are images taken by a mobile device… Yes, then the task of extracting a table from such documents gets even harder… Algodocs comes to the rescue! Extract tables from PDF and scanned documents with Algodocs Algodocs allows you to extract tables from PDF or scanned documents of any complexity thanks to its flexible extracting rules. Additionally, you can convert the table into the format you need with no coding at all. With Algodocs, you can extract invoice line items, purchase order product lists, bank statement transactions, and any other financial or custom documents that contain tables. Algodocs offers a free subscription plan forever with 50 pages per month. You may check our pricing for paid subscriptions based on your document processing requirements. Algodocs has a user-friendly interface and an easy-to-use extracting rules editor. You can set up extracting rules in minutes for extracting tables from your documents. The following are the steps to follow when extracting tables from documents in Algodocs: You may watch the screencast video tutorials below on table extraction from documents. You can check out our Video Tutorials section for more videos. In the following screencast video, we demonstrate how you can extract tables, which are in fixed or variable positions, from PDF or scanned documents. In the following screencast video, we demonstrate how you can extract tables that span over multiple pages in a PDF. In the following screencast video, we demonstrate how you can use the ‘Merge Rows’ filter to extract tables that contain rows with multiple lines. Moreover, you can benefit from integrations in Algodocs such as Google Drive, Dropbox, or Zapier, and automate your document data extraction workflow with Algodocs in minutes. Please contact us if you need any assistance.

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