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Concept mining extracts ideas and concepts from any type of document, useful in evaluating software and AI. It works well with longer documents, allowing for cross-referencing and efficient retrieval of related documents. Customizable software applications aid in identifying concepts and finding logical connections.
Concept mining is a process that focuses on extracting ideas and concepts found in documents. The approach is somewhat similar to text mining, with the main difference being that text mining focuses on extracting information rather than ideas. Concept mining is useful in a number of applications, including the evaluation of software programs and in various applications generally classified as part of the artificial intelligence discipline within computer science.
Concept mining can be used with any type of document, regardless of how they are formatted. This strategy will work well with smaller documents, but is particularly effective with longer documents, as ideas can be extracted throughout the document. This is in contrast to extracting specific sections of text, especially as the words included in the extracted section might take on different meanings based on the context of use. Because concept mining considers all text as a whole, it increases your ability to glean intent and meaning based on the overall flow of the document.
Real-world applications of concept mining include the ability to scan multiple documents in a corporate database and relate them based on concepts found in similar documents. What this helps accomplish is the ability to cross-reference large numbers of documents in ways that are not possible using text mining or other forms of data mining. It is not unusual for companies to use this approach in conjunction with other strategies in order to organize the most efficient and complete processes for accessing related documents with minimal delay.
While the idea of concept mining has been around for decades, this process has become increasingly important as businesses and institutions of all sizes and types rely more heavily on electronic data rather than paper documents. To this end, the development of customizable software applications has also spread to allow the relationship of multiple documents from a conceptual point of view. Most of these software programs are configured to allow for some degree of intuitive activity as a means of identifying concepts found with text and finding logical connections to other documents. When concept mining is managed effectively, this approach to document organization and retrieval can greatly improve your ability to make the best use of archived documents and make retrieval of relevant ideas and tasks much faster and easier.
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