Difference between revisions of "A Novel Method for Clustering Web Search Results with Wikipedia Disambiguation Pages"
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| − | '''A Novel Method for Clustering Web Search Results with Wikipedia Disambiguation Pages''' - scientific work related to Wikipedia quality published in 2015, written by Zhi Huang, Zhendong Niu, Zhendong Niu, Donglei Liu, Wenjuan Niu and Wei Wang. | + | '''A Novel Method for Clustering Web Search Results with Wikipedia Disambiguation Pages''' - scientific work related to [[Wikipedia quality]] published in 2015, written by [[Zhi Huang]], [[Zhendong Niu]], [[Zhendong Niu]], [[Donglei Liu]], [[Wenjuan Niu]] and [[Wei Wang]]. |
== Overview == | == Overview == | ||
| − | Organizing search results of an ambiguous query into topics can facilitate information search on the Web. In this paper, authors propose a novel method to cluster search results of ambiguous query into topics about the query constructed from Wikipedia disambiguation pages (WDP). To improve the clustering result, authors propose a concept filtering method to filter semantically unrelated concepts in each topic. Also, authors propose the top K full relations (TKFR) algorithm to assign search results to relevant topics based on the similarities between concepts in the results and topics. Comparing with the clustering methods whose topic labels are extracted from search results, the topics of WDP which are edited by human are much more helpful for navigation. The experiment results show that method can work for ambiguous queries with different query lengths and highly improves the clustering result of method using WDP. | + | Organizing search results of an ambiguous query into topics can facilitate information search on the Web. In this paper, authors propose a novel method to cluster search results of ambiguous query into topics about the query constructed from [[Wikipedia]] disambiguation pages (WDP). To improve the clustering result, authors propose a concept filtering method to filter semantically unrelated concepts in each topic. Also, authors propose the top K full relations (TKFR) algorithm to assign search results to relevant topics based on the similarities between concepts in the results and topics. Comparing with the clustering methods whose topic labels are extracted from search results, the topics of WDP which are edited by human are much more helpful for navigation. The experiment results show that method can work for ambiguous queries with different query lengths and highly improves the clustering result of method using WDP. |
Revision as of 09:47, 9 July 2019
A Novel Method for Clustering Web Search Results with Wikipedia Disambiguation Pages - scientific work related to Wikipedia quality published in 2015, written by Zhi Huang, Zhendong Niu, Zhendong Niu, Donglei Liu, Wenjuan Niu and Wei Wang.
Overview
Organizing search results of an ambiguous query into topics can facilitate information search on the Web. In this paper, authors propose a novel method to cluster search results of ambiguous query into topics about the query constructed from Wikipedia disambiguation pages (WDP). To improve the clustering result, authors propose a concept filtering method to filter semantically unrelated concepts in each topic. Also, authors propose the top K full relations (TKFR) algorithm to assign search results to relevant topics based on the similarities between concepts in the results and topics. Comparing with the clustering methods whose topic labels are extracted from search results, the topics of WDP which are edited by human are much more helpful for navigation. The experiment results show that method can work for ambiguous queries with different query lengths and highly improves the clustering result of method using WDP.
