Chinese and English search result visualization system based on multi-label classification

Abstract

The invention relates to a Chinese and English search result visualization system based on multi-label classification. The Chinese and English search result visualization system comprises a display module, a search module, a classification module and a visualization module, wherein the display module is used for displaying a user interface and search results; the search module is used for calling a search engine API to perform searching and to obtain the search results according to inquire statements of users, and respectively integrating the Chinese and English search results; the classification module is used for performing Chinese and English multi-label classification on the results obtained through the search module and performing integration on the classification results; and the visualization module is used for achieving Web user interface design on the integrated classification results and outputting through the display module. Compared with the prior art, the Chinese and English search result visualization system can perform effective multi-label classification and integration on the search results by means of granular computing theory in a multi-label classification method based on the Bayesian theory, can display the search results by category according to user requirements by designing the visual system through the method, simultaneously cannot lose the search results, improves user browse efficiency and improves user browse experience.

Description

technical field [0001] The invention relates to the field of information technology, in particular to a Chinese and English search result visualization system based on multi-label classification. Background technique [0002] At present, online electronic documents are growing rapidly, and a large number of documents are uploaded to the Internet every day. Search engines, as an important method of acquiring network knowledge, have been used more and more widely. However, search engines often return a large number of search results, which makes users often submerged in the ocean of information. Current mainstream search engines return search results sorted according to user keywords. In order to find the information of interest, the user needs to browse the search results one by one. [0003] In response to the above problems, some people began to explore more advanced information retrieval methods. Generally speaking, there are two ways: one is the semantic-based informa...

AI Technical Summary

Problems solved by technology

However, such automatically obtained cluster names are often difficult to express the main content of the cluster

This makes it difficult for users to locate the information they are interested in according to the class cluster name given by the system, and the role of this visualization process is not obvious

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