Name
Abstract | ||
|---|---|---|
The interaction of vast numbers of search engine users with sets of search results sets is a potential source of significant quantities of resource classification data. In this paper we discuss work which uses coselection data (i.e. multiple click-through events generated by the same user on a single search engine result page) as an indicator of mutual relevance between web resources and a means for the automatic clustering of sense-singular resources. The results indicate that coselection can be used in this way. We ground-truthed unambiguous query clustering, forming a foundation for work on automatic ambiguity detection based on the resulting number of generated clusters. Using the cluster overlap by population principle, the extension of previous work allowed determination of synonyms or lingual translations where overlapping clusters indicated the mutual relevance in coselection and subsequently the irrelevance of the actual label inherited from the user query. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/1995966.1995972 | HT |
Keywords | Field | DocType |
crowd-sourced coselection,unambiguous query clustering,resource classification data,search results set,implicit association,single search engine result,search engine user,coselection data,mutual relevance,previous work,automatic clustering,automatic ambiguity detection,search engine,ground truth | Web resource,Web search query,Population,Data mining,World Wide Web,Search engine,Information retrieval,Computer science,Cluster analysis,Ambiguity | Conference |
Citations | PageRank | References |
4 | 0.41 | 27 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Helen Ashman | 1 | 767 | 66.74 |
| Michael Antunovic | 2 | 15 | 1.96 |
| Satit Chaprasit | 3 | 4 | 0.41 |
| Gavin Smith | 4 | 43 | 5.31 |
| Mark Truran | 5 | 286 | 14.43 |