Event relevancy calculation method based on associated semantic chain network
An event-related, computational method, applied in computing, semantic analysis, natural language data processing, etc., can solve the problem of not considering the semantic relevance of keywords, loss of text structure information, etc.
Active Publication Date: 2020-02-07
SHANGHAI UNIV +1
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Problems solved by technology
[0003] However, when using the cosine calculation method based on the vector space model to calculate the similarity of events, there are the following shortcomings: the vector space model regards the text as a collection of terms, and regards the relationship between terms and terms as independent, so A large amount of text structure information is lost
The cosine calculation formula does not consider the semantic correlation between keywords in the text
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[0028] Embodiments of the present invention will be further described below in conjunction with the accompanying drawings.
[0029] see figure 1 , the event correlation calculation method based on the associated semantic chain network is characterized in that: the associated semantic chain network of the event is used as the reference object of the correlation degree, and the reference object is quantified from the two aspects of the common keywords and the associated relationship. The degree of relevance of the associated semantic chain network is the measure of the degree of relevance.
[0030] The event-related semantic chain network includes the keywords of the event and the relationship between the keywords, which are expressed as follows:
[0031] EALN=
[0032] Among them, K={k 1 ,k 2 ,...,k n} is the set of event keywords, n is the number of keywords in the network, W is a symmetric correlation matrix of n×n, the element w in row i and column j in this matrix ij ...
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The invention discloses an event relevancy calculation method based on an associated semantic chain network. The method comprises the following specific steps: (1) inputting any two event type text sets in the field; (2) expressing each event type text set as an associated semantic chain network; (3) calculating the relevancy of the event on the keyword; (4) calculating the relevancy of the eventson the incidence relation; and (5) outputting the relevancy of the events. An associated semantic chain network of an event is taken as a reference object of relevancy, the associated semantic chainnetwork comprises keywords of the event and an association relationship between the keywords, and the relationship has a weight. The reference object is quantified from two aspects of the common keyword and the association relationship, and the correlation degree of the associated semantic chain network is taken as the measurement standard of the relevancy. The method is simple, easy to operate and good in effect.
Description
technical field [0001] The invention relates to a method for calculating the correlation degree of an event, in particular to a method for calculating the correlation degree of an event based on an associated semantic chain network. Background technique [0002] At present, the most widely used calculation method of event text relevance is the cosine calculation method based on the vector space model. The vector space model represents the event text as a weight vector, each item in the vector is composed of terms, and the weight of each term is determined by the TFIDF method. The cosine calculation formula calculates the cosine value of the included angle of the text weight vector, and uses it as the event correlation degree. [0003] However, when using the cosine calculation method based on the vector space model to calculate the similarity of events, there are the following shortcomings: the vector space model regards the text as a collection of terms, and regards the re...
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IPC IPC(8): G06F40/30G06F40/289
Inventor 骆祥峰黄敬马秀侠陈雪
Owner SHANGHAI UNIV