Twinder: Enhancing Twitter Search

Ke Tao; Fabian Abel; Claudia Hauff; Geert Jan Houben; Ujwal Gadiraju

doi:10.1007/978-3-642-54798-0_10

Twinder: Enhancing Twitter Search

Ke Tao, Fabian Abel, Claudia Hauff, Geert Jan Houben, Ujwal Gadiraju

Web Information Systems

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

Abstract

How can the search process on Twitter be improved to better meet the various information needs of its users? As an answer to this question, we have developed the Twinder framework, a scalable search system for Twitter streams. Twinder contains algorithms to determine the relevance of tweets in relation to search requests, as well as components to detect (near-)duplicate content, to diversify search results, and to personalize the search result ranking. In this paper, we report on our current progress, including the system architecture and the different modules for solving specific problems. Finally, we empirically determine the effectiveness of Twinder's components with experiments on representative datasets.

Original language	English
Title of host publication	Bridging Between Information Retrieval and Databases - PROMISE Winter School 2013
Subtitle of host publication	Revised Tutorial Lectures
Editors	Nicola Ferro
Place of Publication	Berlin
Publisher	Springer
Pages	208-217
Number of pages	10
ISBN (Electronic)	978-3-642-54798-0
ISBN (Print)	978-3-642-54797-3
DOIs	https://doi.org/10.1007/978-3-642-54798-0_10
Publication status	Published - 2014
Event	2013 PROMISE Winter School: Bridging Between Information Retrieval and Databases - Bressanone, Italy Duration: 4 Feb 2013 → 8 Feb 2013

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8173
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2013 PROMISE Winter School: Bridging Between Information Retrieval and Databases
Country/Territory	Italy
City	Bressanone
Period	4/02/13 → 8/02/13

Keywords

Exact Copy
Relevance Estimation
Retrieval Score
Cloud Computing Infrastructure
Microblog Post

Access to Document

10.1007/978-3-642-54798-0_10

Cite this

Tao, K., Abel, F., Hauff, C., Houben, G. J., & Gadiraju, U. (2014). Twinder: Enhancing Twitter Search. In N. Ferro (Ed.), Bridging Between Information Retrieval and Databases - PROMISE Winter School 2013: Revised Tutorial Lectures (pp. 208-217). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8173). Springer. https://doi.org/10.1007/978-3-642-54798-0_10

Tao, Ke ; Abel, Fabian ; Hauff, Claudia et al. / Twinder : Enhancing Twitter Search. Bridging Between Information Retrieval and Databases - PROMISE Winter School 2013: Revised Tutorial Lectures. editor / Nicola Ferro. Berlin : Springer, 2014. pp. 208-217 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{12c038d836ed4fb394ca58f17f79fee5,

title = "Twinder: Enhancing Twitter Search",

abstract = "How can the search process on Twitter be improved to better meet the various information needs of its users? As an answer to this question, we have developed the Twinder framework, a scalable search system for Twitter streams. Twinder contains algorithms to determine the relevance of tweets in relation to search requests, as well as components to detect (near-)duplicate content, to diversify search results, and to personalize the search result ranking. In this paper, we report on our current progress, including the system architecture and the different modules for solving specific problems. Finally, we empirically determine the effectiveness of Twinder's components with experiments on representative datasets.",

keywords = "Exact Copy, Relevance Estimation , Retrieval Score, Cloud Computing Infrastructure, Microblog Post",

author = "Ke Tao and Fabian Abel and Claudia Hauff and Houben, {Geert Jan} and Ujwal Gadiraju",

year = "2014",

doi = "10.1007/978-3-642-54798-0_10",

language = "English",

isbn = "978-3-642-54797-3",

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

publisher = "Springer",

pages = "208--217",

editor = "Nicola Ferro",

booktitle = "Bridging Between Information Retrieval and Databases - PROMISE Winter School 2013",

note = "2013 PROMISE Winter School: Bridging Between Information Retrieval and Databases ; Conference date: 04-02-2013 Through 08-02-2013",

}

Tao, K, Abel, F, Hauff, C, Houben, GJ & Gadiraju, U 2014, Twinder: Enhancing Twitter Search. in N Ferro (ed.), Bridging Between Information Retrieval and Databases - PROMISE Winter School 2013: Revised Tutorial Lectures. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8173, Springer, Berlin, pp. 208-217, 2013 PROMISE Winter School: Bridging Between Information Retrieval and Databases, Bressanone, Italy, 4/02/13. https://doi.org/10.1007/978-3-642-54798-0_10

Twinder: Enhancing Twitter Search. / Tao, Ke; Abel, Fabian; Hauff, Claudia et al.
Bridging Between Information Retrieval and Databases - PROMISE Winter School 2013: Revised Tutorial Lectures. ed. / Nicola Ferro. Berlin: Springer, 2014. p. 208-217 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8173).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Twinder

T2 - 2013 PROMISE Winter School: Bridging Between Information Retrieval and Databases

AU - Tao, Ke

AU - Abel, Fabian

AU - Hauff, Claudia

AU - Houben, Geert Jan

AU - Gadiraju, Ujwal

PY - 2014

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N2 - How can the search process on Twitter be improved to better meet the various information needs of its users? As an answer to this question, we have developed the Twinder framework, a scalable search system for Twitter streams. Twinder contains algorithms to determine the relevance of tweets in relation to search requests, as well as components to detect (near-)duplicate content, to diversify search results, and to personalize the search result ranking. In this paper, we report on our current progress, including the system architecture and the different modules for solving specific problems. Finally, we empirically determine the effectiveness of Twinder's components with experiments on representative datasets.

AB - How can the search process on Twitter be improved to better meet the various information needs of its users? As an answer to this question, we have developed the Twinder framework, a scalable search system for Twitter streams. Twinder contains algorithms to determine the relevance of tweets in relation to search requests, as well as components to detect (near-)duplicate content, to diversify search results, and to personalize the search result ranking. In this paper, we report on our current progress, including the system architecture and the different modules for solving specific problems. Finally, we empirically determine the effectiveness of Twinder's components with experiments on representative datasets.

KW - Exact Copy

KW - Relevance Estimation

KW - Retrieval Score

KW - Cloud Computing Infrastructure

KW - Microblog Post

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DO - 10.1007/978-3-642-54798-0_10

M3 - Conference contribution

AN - SCOPUS:84901294701

SN - 978-3-642-54797-3

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

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ER -

Tao K, Abel F, Hauff C, Houben GJ , Gadiraju U. Twinder: Enhancing Twitter Search. In Ferro N, editor, Bridging Between Information Retrieval and Databases - PROMISE Winter School 2013: Revised Tutorial Lectures. Berlin: Springer. 2014. p. 208-217. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-54798-0_10

Twinder: Enhancing Twitter Search

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