Learning adaptive domain models from click data to bootstrap interactive web search

Deirdre Lungley; Udo Kruschwitz; Dawei Song

doi:10.1007/978-3-642-28997-2_56

Learning adaptive domain models from click data to bootstrap interactive web search

Deirdre Lungley^*
, Udo Kruschwitz
, Dawei Song

^*此作品的通讯作者

University of Essex
Robert Gordon University

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

Today, searchers exploring the World Wide Web have come to expect enhanced search interfaces-query completion and related searches have become standard. Here we propose a Formal Concept Analysis lattice as an underlying domain model to provide a source of query refinements. The initial lattice is constructed using NLP. User clicks on documents, seen as implicit user feedback, are harnessed to adapt it. In this paper, we explore the viability of this adaptation process and the results we present demonstrate its promise and limitations for proposing initial effective refinements when searching the diverse WWW domain.

源语言	英语
主期刊名	Advances in Information Retrieval - 34th European Conference on IR Research, ECIR 2012, Proceedings
页	527-530
页数	4
DOI	https://doi.org/10.1007/978-3-642-28997-2_56
出版状态	已出版 - 2012
已对外发布	是
活动	34th European Conference on Information Retrieval, ECIR 2012 - Barcelona, 西班牙期限: 1 4月 2012 → 5 4月 2012

丛书

姓名	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷	7224 LNCS
ISSN（印刷版）	0302-9743
ISSN（电子版）	1611-3349

会议

会议	34th European Conference on Information Retrieval, ECIR 2012
国家/地区	西班牙
市	Barcelona
时期	1/04/12 → 5/04/12

访问文件

10.1007/978-3-642-28997-2_56

其它文件与链接

链接到 Scopus 的出版物

引用此

Lungley, D., Kruschwitz, U., & Song, D. (2012). Learning adaptive domain models from click data to bootstrap interactive web search. 在 Advances in Information Retrieval - 34th European Conference on IR Research, ECIR 2012, Proceedings (页码 527-530). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 7224 LNCS). https://doi.org/10.1007/978-3-642-28997-2_56

Lungley, Deirdre ; Kruschwitz, Udo ; Song, Dawei. / Learning adaptive domain models from click data to bootstrap interactive web search. Advances in Information Retrieval - 34th European Conference on IR Research, ECIR 2012, Proceedings. 2012. 页码 527-530 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{2c39678315d7442ea44ed2fad58e6a6a,

title = "Learning adaptive domain models from click data to bootstrap interactive web search",

abstract = "Today, searchers exploring the World Wide Web have come to expect enhanced search interfaces-query completion and related searches have become standard. Here we propose a Formal Concept Analysis lattice as an underlying domain model to provide a source of query refinements. The initial lattice is constructed using NLP. User clicks on documents, seen as implicit user feedback, are harnessed to adapt it. In this paper, we explore the viability of this adaptation process and the results we present demonstrate its promise and limitations for proposing initial effective refinements when searching the diverse WWW domain.",

keywords = "Domain Modelling, Formal Concept Analysis, Query Refinement, Usage Mining",

author = "Deirdre Lungley and Udo Kruschwitz and Dawei Song",

year = "2012",

doi = "10.1007/978-3-642-28997-2\_56",

language = "English",

isbn = "9783642289965",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "527--530",

booktitle = "Advances in Information Retrieval - 34th European Conference on IR Research, ECIR 2012, Proceedings",

note = "34th European Conference on Information Retrieval, ECIR 2012 ; Conference date: 01-04-2012 Through 05-04-2012",

}

Lungley, D, Kruschwitz, U & Song, D 2012, Learning adaptive domain models from click data to bootstrap interactive web search. 在 Advances in Information Retrieval - 34th European Conference on IR Research, ECIR 2012, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 卷 7224 LNCS, 页码 527-530, 34th European Conference on Information Retrieval, ECIR 2012, Barcelona, 西班牙, 1/04/12. https://doi.org/10.1007/978-3-642-28997-2_56

Learning adaptive domain models from click data to bootstrap interactive web search. / Lungley, Deirdre; Kruschwitz, Udo; Song, Dawei.
Advances in Information Retrieval - 34th European Conference on IR Research, ECIR 2012, Proceedings. 2012. 页码 527-530 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 7224 LNCS).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Learning adaptive domain models from click data to bootstrap interactive web search

AU - Lungley, Deirdre

AU - Kruschwitz, Udo

AU - Song, Dawei

PY - 2012

Y1 - 2012

N2 - Today, searchers exploring the World Wide Web have come to expect enhanced search interfaces-query completion and related searches have become standard. Here we propose a Formal Concept Analysis lattice as an underlying domain model to provide a source of query refinements. The initial lattice is constructed using NLP. User clicks on documents, seen as implicit user feedback, are harnessed to adapt it. In this paper, we explore the viability of this adaptation process and the results we present demonstrate its promise and limitations for proposing initial effective refinements when searching the diverse WWW domain.

AB - Today, searchers exploring the World Wide Web have come to expect enhanced search interfaces-query completion and related searches have become standard. Here we propose a Formal Concept Analysis lattice as an underlying domain model to provide a source of query refinements. The initial lattice is constructed using NLP. User clicks on documents, seen as implicit user feedback, are harnessed to adapt it. In this paper, we explore the viability of this adaptation process and the results we present demonstrate its promise and limitations for proposing initial effective refinements when searching the diverse WWW domain.

KW - Domain Modelling

KW - Formal Concept Analysis

KW - Query Refinement

KW - Usage Mining

UR - https://www.scopus.com/pages/publications/84860196674

U2 - 10.1007/978-3-642-28997-2_56

DO - 10.1007/978-3-642-28997-2_56

M3 - Conference contribution

AN - SCOPUS:84860196674

SN - 9783642289965

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 527

EP - 530

BT - Advances in Information Retrieval - 34th European Conference on IR Research, ECIR 2012, Proceedings

T2 - 34th European Conference on Information Retrieval, ECIR 2012

Y2 - 1 April 2012 through 5 April 2012

ER -

Lungley D, Kruschwitz U, Song D. Learning adaptive domain models from click data to bootstrap interactive web search. 在 Advances in Information Retrieval - 34th European Conference on IR Research, ECIR 2012, Proceedings. 2012. 页码 527-530. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-28997-2_56

Learning adaptive domain models from click data to bootstrap interactive web search

摘要

丛书

会议

访问文件

其它文件与链接

学术指纹

引用此