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This tutorial demonstrates how to use Apache Tika in a Java project to parse PDF, Word, and text documents, extract specific fields such as name and ID number, and shows the required Maven dependencies and sample code for performing the extraction.
This article demonstrates how to add Apache Tika dependencies to a Spring Boot project, configure tika-config.xml, create a Java configuration class, and use the injected Tika bean to detect, translate, and parse various document formats such as PDF, PPT, and XLS.
This article introduces Apache Tika for document parsing, outlines its key advantages, and provides step‑by‑step Spring Boot 3 examples—including facade parsing, text, PDF, auto‑detect, HTML conversion, custom configuration, and file‑upload integration—complete with code snippets and output screenshots.
This guide shows how to integrate Apache Tika into a Spring Boot application, covering Maven dependencies, XML configuration, a Spring @Configuration class, and usage of Tika’s detection and parsing APIs for processing various document formats.
This guide demonstrates how to add Apache Tika to a Spring Boot project by declaring the tika‑bom, core and parser dependencies, providing a custom tika‑config.xml, creating a @Configuration class that builds a Tika bean, and then injecting the bean to detect, parse, or translate documents.
This article explains intelligent document processing (IDP) by describing its core components—OCR, document parsing, and information extraction—detailing various OCR and text‑detection algorithms, discussing document layout reconstruction, table parsing, domain‑specific model adaptation, system optimization, and productization challenges, and outlining future research directions.