In such applications, the documents are classified based on the prominent terms in the extracted content of the document. In the field of artificial intelligence, there are certain tools to analyze documents automatically at semantic level and extract all kinds of data from them. Apart from this, the search engine uses the extracted content in many other ways as well. The extracted content is then passed to the indexer of the search engine that uses it to build a search index. Such extracted content and metadata are very useful for a search engine. The duty of extraction component is to extract the text and metadata from the document. Thereafter, the crawler transfers these indexed documents to an extraction component. Search engines are information processing systems designed to search information and indexed documents from the Web.Ĭrawler is an important component of a search engine that crawls through the Web to fetch the documents that are to be indexed using some indexing technique. Tika is widely used while developing search engines to index the text contents of digital documents. Here we will discuss a few prominent applications that depend heavily on Apache Tika. There are various applications that make use of Apache Tika. Apache Tika serves this purpose by providing a generic API to locate and extract data from multiple file formats. Therefore, applications such as search engines and content management systems need additional support for easy extraction of data from these document types. Data is being stored in various formats such as text documents, excel spreadsheet, PDFs, images, and multimedia files, to name a few. It uses existing specialized parser libraries for each document type.Īll these parser libraries are encapsulated under a single interface called the Parser interface.Īccording to, there are about 15k to 51k content types, and this number is growing day by day. Tika provides a single generic API for parsing different file formats. Using Tika, one can develop a universal type detector and content extractor to extract both structured text as well as metadata from different types of documents such as spreadsheets, text documents, images, PDFs and even multimedia input formats to a certain extent. Internally, Tika uses existing various document parsers and document type detection techniques to detect and extract data. Apache Tika is a library that is used for document type detection and content extraction from various file formats.
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