Method for recommending documents based on tags and document recommending device

Abstract

The invention discloses a method for recommending documents based on tags and a document recommending device. The method comprises the following steps of: receiving a document tag selected by a user, searching a previously set synonym word collection and obtaining a synonym group corresponding to the document tag; according to the obtained synonym group, searching and obtaining a document list containing the synonym group from a previously stored document library; calculating the characteristic value of each document in the document list containing the synonym group, and constructing a space weight vector based on the document tag; and according to the constructed space weight vector based on the document tag, calculating the similarity of documents corresponding to the document tag with each document in the document list, selecting a preset number of documents with the highest similarity as searched results and outputting the searched results. Through the application of the method and the device, the document recommending efficiency can be increased.

Description

technical field [0001] The present invention relates to search technology, in particular to a method for recommending documents based on tags (tags) and a document recommending device. Background technique [0002] With the rapid development of Internet technology, the number of network documents, such as blog posts and micro-blog posts, is rapidly expanding. How to effectively manage the massive data resources of network documents, and how to effectively recommend documents to users from the documents of massive data resources, has received increasing attention. more and more attention. Among them, document classification technology, as a key technology for managing massive data and recommending documents, has been greatly developed. High-quality document classification can provide better support for managing and recommending documents. [0003] In the prior art, document classification is mainly based on eigenvalue weighting technology, and the calculation of eigenvalue w...

AI Technical Summary

Problems solved by technology

In this way, there may be no document matching the recommended phrase "Congratulations for a long time" in the document library of the search engine, so that the recommendation fails and the recommendation efficiency is low, without considering the synonymous expansion of the recommended words, for example, the recommended words are respectively "Congratulations" is synonymously expanded to obtain the synonymous recommended phrase "Congratulations Congratulations Hexi"; the recommended word "Jiuyang" is synonymously expanded to obtain the synonymous recommended phrase "Jiuyangjiuyang daimyojiumushengming"; "Extend synonymously to get the synonymous recommended word phrase "excellent praise", and then use the expanded synonymous phrase as the coordinate of a spatial weight vector to search and query, so as to obtain documents related to the query obtained through the query string query (similar to ) documents as recommended documents to expand the amount of information in the query results and meet the user's query requirements for synonyms

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