Text search method and system

Abstract

The invention provides a text search method. The text search method comprises the following steps that an inquiry statement is divided into a key semanteme and a key word according to the input inquiry statement, semantic extension based on the domain ontology is carried out according to the key semanteme so that the extended semanteme can be generated, an extended inquiry statement is generated according to the extended semanteme and the key word, similarity grading is carried out on the extended semanteme, semantic weighing is carried out on the extended inquiry statement, text search is carried out on the extended inquiry statement so as to obtain the corresponding inquiry result, and the searched inquiry result is displayed. According to the method, the search recall ratio and the precision ratio of a search engine can be increased in the text search process. The invention further provides a text search system.

Description

technical field [0001] The invention relates to the technical field of data intelligent processing and analysis, in particular to a text retrieval method and system. Background technique [0002] For text search and catalog retrieval, the current main method is to determine whether they match according to the keywords of the search object, that is, to divide the search sentence into keywords and search separately, but the machine cannot understand human language, so it cannot understand the query intent , resulting in inaccurate search information. For example, if you search for "African American President", the search intent is "Obama", but the result contains keywords such as "America", "Black", "President" and so on. And the actual search sentence basically only includes one or two keywords, regardless of the semantics, it is difficult to deal with the problem that the same keyword has different meanings or different keywords have the same meaning, which makes it easy fo...

AI Technical Summary

Problems solved by technology

The synonym retrieval algorithm is to perform a matching operation on each related word in the search range of the thesaurus to obtain an optimal result, but this kind of matching cannot express complex relationships such as classification and reference of vocabulary, and there is no dynamic reasoning feature at the same time

[0004] Semantic retrieval can understand the logical relationship between keywords, which greatly improves the retrieval efficiency, but the current semantic research is too cumbersome, and it is often difficult to combine it with the current technology

So far, there is still no unified definition of semantic retrieval, so ontology-based semantic retrieval mostly stays in theoretical research, with few real examples

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