Clustering web people search results using fuzzy ants

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Clustering web people search results using fuzzy ants
Person name queries often bring up web pages that correspond to individuals sharing the same name. The Web People Search (WePS) task consists of organizing search results for ambiguous person name queries into meaningful clusters, with each cluster referring to one individual. This paper presents a fuzzy ant based clustering approach for this multi-document person name disambiguation problem. The main advantage of fuzzy ant based clustering, a technique inspired by the behavior of ants clustering dead nestmates into piles, is that no speciļ¬cation of the number of output clusters is required. This makes the algorithm very well suited for the Web Person Disambiguation task, where we do not know in advance how many individuals each person name refers to. We compare our results with state-of-the-art partitional and hierarchical clustering approaches (k-means and Agnes) and demonstrate favorable results. This is particularly interesting as the latter involve manual setting of a similarit...
Els Lefever, Timur Fayruzov, Véronique Host
Added 28 Jan 2011
Updated 28 Jan 2011
Type Journal
Year 2010
Where ISCI
Authors Els Lefever, Timur Fayruzov, Véronique Hoste, Martine De Cock
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