Name
Abstract | ||
|---|---|---|
Today's major search engines return ranked search results that match the keywords the user specifies. There have been many proposals to rank the search results such that they match the user's intentions and needs more closely. Despite good advances during the past decade, this problem still requires considerable research, as the number of search results has become ever larger. We define the collection of each search result and all the Web pages that are linked to the result as a search-result drilldown. We hypothesize that by mining and analyzing the top terms in the search-result drilldown of search results, it may be possible to make each search result more meaningful to the user, so that the user may select the desired search results with higher confidence. In this paper, we describe this technique, and show the results of preliminary validation work that we have done. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.eswa.2009.02.074 | Expert Syst. Appl. |
Keywords | Field | DocType |
refining search results,past decade,major search engine,considerable research,refining search result,web page,top term,mining framework,preliminary validation work,top terms,search-result drilldown,higher confidence,keyword-based search,search result,good advance,search engine,web pages | Data mining,Web search query,Incremental heuristic search,Organic search,Search engine,Information retrieval,Phrase search,Semantic search,Computer science,Beam search,Search analytics | Journal |
Volume | Issue | ISSN |
36 | 8 | Expert Systems With Applications |
Citations | PageRank | References |
2 | 0.36 | 21 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ok-Ran Jeong | 1 | 181 | 22.02 |
| Eunseok Lee | 2 | 227 | 47.07 |
| Won Kim | 3 | 14 | 3.26 |