Semantics vein document searching method

Abstract

The invention discloses a discloses a document searching method based on semantics, which is applied to document searching, in particular to network document searching. The method includes the steps of converting the searching requirements inputted by a user into searching semantics veins, which represents to discompose the inputted searching sentences into different key words and structure relationship; then marking the searched documents according to key wards, sentences separators and pronouns, and replacing the key wards, sentences separators and pronouns into corresponding key words according to a pronoun reference relationship; finally implementing matching test on each sentence of searched semantics veins and tested documents according to the setting of the user on the key words and structure relationship; as only as one sentence matched with the searched semantics veins exists in the tested document, then the document is the document needed by the user. The method does not need to implement complex semantic analysis on the document, has a low development difficulty, and is consistent with the currently universal key word searching using method.

Description

Technical field [0001] The present invention relates to a computer retrieval method for document query through semantic analysis. In particular, the query request input by a user can be converted into a semantic context statement expressing the user's document query intention in the document query, and then the semantic context can be used for retrieval. Traditional keyword query is different from semantic query methods such as semantic network and ontology. Background technique [0002] Computer-based documents, namely electronic document query, especially web document query, play an important role in people's daily life and scientific research work. At present, although there are many well-known query engines, such as Baidu and Sohu, which provide great convenience for querying documents, due to the large number of articles on the Internet, users often encounter information confusion and information overload when searching documents. Problems such as mismatch with words greatl...

AI Technical Summary

Problems solved by technology

[0011] Although there are already very powerful semantic processing tools, due to the huge number of web pages and the inability to realize machine understanding of natural language, the work results of the second level can only stay in the laboratory at present, and the practical value is relatively small

[0012] By using keywords "query" and "semantics" on the patent retrieval web page of the State Intellectual Property Office to search, the semantic context document query method proposed by the present invention was not found

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