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Improvement of Linked Data Fusion Algorithm Based on Bag of Words

Tian Ye Zhang Jingbei   

  • Online:2016-12-15 Published:2016-12-25

Abstract:

Bag of words model is one of the most primitive linked data fusion algorithm, but the algorithm does not use its own semantic keyword for matching and corpus is inadequate, resulting in low accuracy rate of entity link.This paper proposes the use of semantic knowledge base, the use of semantic extension
and loop iterations to enhance the speed and accuracy of entity disambiguation. The algorithm includes two processes. First, linked data sets should go through preliminary semantic integration, on the basis of which, the proposed s-i-BoW algorithm should be utilized to remove the entity ambiguation and links. After comparing with the result received from traditional bag of words model, the paper proves the better effect and efficiency of the proposed s-i-BoW algorithm.

Key words: Bag of words model, BoW, Linked data fusion, Entity links, Entity disambiguation