Agricultural field ontology library based semantic retrieval system and method

Abstract

The invention relates to an agricultural field ontology library based semantic retrieval system and method, belonging to the technical field of intelligent retrieval. In order to improve the accuracy and the efficiency of an agricultural field information semantic retrieval process, only the useful structured data in a webpage are extracted by using an information extraction technology and used as the basic resource for retrieving, thus the structural property and the accuracy of the retrieval data source are greatly ensured in the stage of the basic resource of data; and then the comprehensive and professional agricultural-industry oriented ontology library is established, the semantic extension and inference is carried out according to the inquiry request of the user on the basis of a semantic ontology inference engine through the participation of the user, and the natural language submitted by the user is processed or the extension result is returned to the user once again so that the weight of each ontology example in a semantic extension set can be determined accurately in the participation process of the user, the extended ontology example set meets the inquiry requirement of the user, and further the final retrieval precision and recall rate are improved.

Description

technical field [0001] The invention belongs to the technical field of intelligent retrieval, and in particular relates to a semantic retrieval system and method based on an ontology database in the agricultural field. Background technique [0002] With the continuous emergence of agricultural websites on the Internet, agricultural knowledge and data resources have shown a trend of massive growth. These complex, scattered, heterogeneous and closed agricultural information resources have led to the problem of low utilization of agricultural information resources, forming the current paradoxical phenomenon of Internet information explosion and lack of effective information for agricultural users. Many general search engines, such as Google, Baidu, etc., provide solutions for the retrieval of information resources to a certain extent. However, on the one hand, general search engines are oriented to all industries, and the accuracy and relevance of information retrieval for spe...

AI Technical Summary

Problems solved by technology

On the one hand, basic data resources often contain a large amount of irrelevant redundant information. For example, there are often garbage information such as advertisements, navigation, and copyrights in web pages. If these garbage information is not cleaned, it will bring great noise interference to the later retrieval. ; On the other hand, all the web pages contain semi-structured data, and the really useful data is mixed with html tags, which also greatly reduces the accuracy of retrieval

[0011] At the same time, when the existing technical solutions process the natural query language input by the user, if the natural query sentence input by the user includes ontology concepts, then the matching judgment of the sentence pattern is performed, and whether the matching is successful or not, it is directly Matching or semantically extended ontology concepts to query, due to the lack of user participation in the whole process, the semantic analysis of the natural query language input by the user cannot fully and accurately understand the user's query intention, therefore, it is bound to cause the final The accuracy of query results is not satisfactory

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