Automatic extraction of user's search intention from web search logs
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, Kinam | - |
dc.contributor.author | Jee, Hyesung | - |
dc.contributor.author | Lee, Taemin | - |
dc.contributor.author | Jung, Soonyoung | - |
dc.contributor.author | Lim, Heuiseok | - |
dc.date.accessioned | 2021-09-06T13:54:25Z | - |
dc.date.available | 2021-09-06T13:54:25Z | - |
dc.date.created | 2021-06-15 | - |
dc.date.issued | 2012-11 | - |
dc.identifier.issn | 1380-7501 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/107094 | - |
dc.description.abstract | Web search users complain of the inaccurate results produced by current search engines. Most of these inaccurate results are due to a failure to understand the user's search goal. This paper proposes a method to extract users' intentions and to build an intention map representing these extracted intentions. The proposed method makes intention vectors from clicked pages from previous search logs obtained on a given query. The components of the intention vector are weights of the keywords in a document. It extracts user's intentions by using clustering the intention vectors and extracting intention keywords from each cluster. The extracted the intentions on a query are represented in an intention map. For the efficiency analysis of intention map, we extracted user's intentions using 2,600 search log data a current domestic commercial search engine. The experimental results with a search engine using the intention maps show statistically significant improvements in user satisfaction scores. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | SPRINGER | - |
dc.title | Automatic extraction of user's search intention from web search logs | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Park, Kinam | - |
dc.contributor.affiliatedAuthor | Jung, Soonyoung | - |
dc.contributor.affiliatedAuthor | Lim, Heuiseok | - |
dc.identifier.doi | 10.1007/s11042-010-0723-8 | - |
dc.identifier.scopusid | 2-s2.0-84864026563 | - |
dc.identifier.wosid | 000306345000009 | - |
dc.identifier.bibliographicCitation | MULTIMEDIA TOOLS AND APPLICATIONS, v.61, no.1, pp.145 - 162 | - |
dc.relation.isPartOf | MULTIMEDIA TOOLS AND APPLICATIONS | - |
dc.citation.title | MULTIMEDIA TOOLS AND APPLICATIONS | - |
dc.citation.volume | 61 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 145 | - |
dc.citation.endPage | 162 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Software Engineering | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.subject.keywordAuthor | Search engine | - |
dc.subject.keywordAuthor | Intention map | - |
dc.subject.keywordAuthor | User&apos | - |
dc.subject.keywordAuthor | s search log | - |
dc.subject.keywordAuthor | Clustering | - |
dc.subject.keywordAuthor | Knowledge representation | - |
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