Bayesian word sense disambiguation method based on synonym expansion
A technology of word sense disambiguation and synonym word forest, applied in the field of natural language processing, can solve the problems of poor disambiguation effect, time-consuming and laborious disambiguation knowledge, etc., to achieve the effect of improving accuracy, alleviating the problem of data sparseness, and broad development prospects.
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[0040] figure 1 It is a schematic diagram of the entire method of the present invention, and a specific implementation scheme will be given below in conjunction with examples. "all unit The work of the team members has been completed" for the training corpus, the sentence" unit Personnel did not issue a distress signal" is the test corpus, and the ambiguity word "crew" in the test corpus is disambiguated.
[0041] The whole implementation process is as follows:
[0042] (1) Expand the context of the training corpus by using the synonym Cilin to generate a pseudo-training corpus.
[0043] The ambiguous sentence is expanded by using the synonym Cilin to obtain the set of context synonyms. For example, "all, all, everything, the whole", "personnel, team members, team members, party members", "tasks, responsibilities, full-time, vocation" and so on. The above set of synonyms, the ambiguous word "crew" and the meaning of the ambiguous word "personnel" together constitute the...
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