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- W2381050669 abstract "Vector space model,which calculates the relatedness between documents through word frequency,is a frequently used information retrieval model. This method can meet the user's basic retrieval requirements,but for users with higher requirements,its effect is still not very ideal. In this paper,based on vector space model,first calculate the similarity,which can produce words related to the query word,between words through the use of domain ontology and upper ontology. So can take advantage of the related word when calculate TF and IDF. Then by introducing the concept of word order relatedness and word adjacent relatedness,can embody the position relationship. The experimental results showthat this method can improve the precision considerably. This fully shows that,compared with the original vector space model,the retrieval model proposed not only considers the terms which have similar semantics with the original words,but also thinks about the word order information and word adjacent information,thus can meet users' retrieval requirements better." @default.
- W2381050669 created "2016-06-24" @default.
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- W2381050669 date "2015-01-01" @default.
- W2381050669 modified "2023-09-23" @default.
- W2381050669 title "Information Retrieval Model Based on Domain Ontology and Position Relationship" @default.
- W2381050669 hasPublicationYear "2015" @default.
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