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712results about How to "Improve search capabilities" patented technology

Semantic query expansion method based on domain knowledge

The invention discloses a semantic query expansion method based on domain knowledge, which comprises the following steps: taking concept expression and a knowledge tree system as the basis to construct the domain knowledge; performing primary semantic analysis on query phases input by users to form a semantic item list; utilizing results of the primary semantic analysis and taking the domain knowledge as the basis to construct a semantic map with expansion types and expansion weights; respectively computing semantic distances between each vertex and an initial vertex in the semantic map; determining an expandable item of each item in the semantic item list according to the semantic distances; and finally, combining all expandable items according to AND / OR logic relations to obtain a semantic item set representing the query intension of the users, and submitting the semantic item set to a searching system for searching. In the semantic query expansion method based on the domain knowledge, the computing time is short, the domain knowledge is fully utilized, and newly-added expanded semantic items and the original query phases have definite semantic relations, and the recall ratio and the precision ratio of the searching system can be improved effectively.
Owner:INST OF AUTOMATION CHINESE ACAD OF SCI

Keyword extracting method based on Word2Vec and Query log

The invention discloses a keyword extracting method based on Word2Vec and a Query log, and relates to the field of information processing. The method includes the steps of S1, building a specific word list of a target field; S2, obtaining candidate keywords of documents in a document set; S3, obtaining word vectors of a plurality of dimensions of each candidate keyword; S4, calculating the cosine similarities between the word vectors of any candidate keyword L and a center vector, judging whether the candidate keyword L exists in the specific word list or not, if the candidate keyword L exists in the specific word list, directly implementing the step S5, and if the candidate keyword L does not exist in the specific word list, directly implementing the step S6; S5, multiplying the obtained cosine similarities by a weighting factor i to obtain new cosine similarities, and implementing the step S6; S6, ranking the values of the cosine similarities from large to small, outputting the values of m cosine similarities from the cosine similarity with the largest value, and obtaining final keywords. By means of the keyword extracting method, the keywords with the ideal quality can be rapidly and efficiently extracted for texts in specific fields, oral words are prevented from being introduced, and the extracted keywords are high in quality.
Owner:CHEZHI HULIAN BEIJING SCI & TECH CO LTD
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