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- W2384644275 abstract "Named entity mining from query log aims to mine a list of named entities with the specific type from the query log.Previous work proposed a seed-based method which ranked the candidate entities based on the similarity between the template distribution of the specified class and that of the entities.However,it doesn't take into account the ambiguity of named entity,the polysemy of the template and the unlabeled data.In this paper,we propose a semi-supervised topic model,which leverages the relationship between the templates(i.e.the co-occurrence between templates) to learn the template distribution of the specified class so as to improve the entity ranking.Experimental results show the effectiveness of the proposed method." @default.
- W2384644275 created "2016-06-24" @default.
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- W2384644275 date "2012-01-01" @default.
- W2384644275 modified "2023-09-27" @default.
- W2384644275 title "Named Entity Mining from Query Log through Semi-supervised Topic Modeling" @default.
- W2384644275 hasPublicationYear "2012" @default.
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