Semantic information retrieval method

A semantic information and semantic distance technology, applied in the Internet field, can solve problems such as lack of processing, affect information retrieval efficiency, and fail to meet the requirements of probability and statistical model data irrelevance, so as to achieve efficient information retrieval and improve accuracy

Active Publication Date: 2014-12-10
吴晨
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AI Technical Summary

Problems solved by technology

[0004] However, these methods all take words as processing objects without exception, and regard them as discrete symbols independent of each other, that is, the appearance of a word is independent of the appearance of other words, so there is inevitably a lack of processing. Data collections with chapters as units and words as units cannot meet the requirements of probability and statistics models for data independence
This has become a bottleneck affecting the further improvement of the current information retrieval efficiency

Method used

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Embodiment Construction

[0020] In order to make the objectives, technical solutions, and advantages of the present invention clearer, the following further describes the embodiments of the present invention in detail with reference to the accompanying drawings:

[0021] This embodiment provides an information retrieval method. As shown in FIG. 1, the method includes:

[0022] Step 10: Receive the query term submitted by the user, and obtain the keywords contained in the query term through word segmentation processing;

[0023] The query term can be a single word or multiple words or phrases, or multiple words (or phrases) connected by relational operators (and, or, etc.). Through word segmentation, the keywords contained in the query are obtained, and stop words are filtered out, such as: yes, yes.

[0024] Step 20: Perform query analysis based on the semantic relationship between the keywords, and convert the keywords into conceptual expressions;

[0025] First, read the keywords obtained in the above steps ...

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Abstract

The invention discloses a semantic information retrieval method. The method includes: receiving query terms submitted by a user, and performing term segmentation to obtain keywords included in the query terms; according to semantic relation among the keywords, performing query analysis and converting the query terms into conceptual expressions; reading texts to be retrieved from a storage medium by taking piece as unit; subjecting the texts to be retrieved to sentence segmentation and term segmentation, and segmenting the read texts into sentences and terms; subjecting the sentences to semantic analysis to obtain conceptual categories of the sentences and conceptual expressions of the terms; computing semantic distance between the acquired conceptual expressions of the query terms and the conceptual expressions of the texts to be retrieved; sorting from the near to the distant according to the semantic distance, and returning query results. Compared with retrieval results obtained by term matching according to a traditional information retrieval method, retrieval results can be effectively improved in accuracy.

Description

technical field [0001] The invention relates to the technical field of the Internet, in particular to a semantic information retrieval method. Background technique [0002] The development of information retrieval has gone through two generations. The first generation of information retrieval is manual category retrieval; the second generation is automatic information retrieval with keyword retrieval as the main performance, which is realized by computer relying on algorithms. The main technical feature of the second-generation search is the success of the probability and statistics algorithm in the search. The emergence of this technology is undoubtedly an important milestone in the development of retrieval technology. The basic method is to segment the text, construct a text feature vector with words as features, and establish an inverted index for query matching. On the other hand, the retrieval request input by the user is also expressed as a feature vector, and the co...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/95G06F40/30
Inventor 吴晨
Owner 吴晨
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