Polyrepresentative clustering: a study of simulated user strategies and representations

Muhammad Kamran Abbasi; Ingo Frommholz

Polyrepresentative clustering: a study of simulated user strategies and representations

Muhammad Kamran Abbasi
, Ingo Frommholz

Institute for Research in Applicable Computing (IRAC)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

The principle of polyrepresentation and document clustering are two established methods for Interactive Information Retrieval, which have been used separately so far. In this paper we discuss a cluster based polyrepresentation approach for information need and document based representations. In our work we simulate and evaluate two possible cluster browsing strategies a user could apply to explore the polyrepresentative clusters. In our evaluation we apply information need and bibliographic features on the iSearch collection. Our results suggest that polyrepresentative cluster browsing may be more effective than exploring a ranked list.

Original language	English
Title of host publication	CEUR Workshop Proceedings
Publisher	CEUR-WS
Pages	47-54
Volume	1344
Edition	Vol 1344
Publication status	Published - 31 Dec 2015
Event	2nd Workshop on Bibliometric-Enhanced Information Retrieval, BIR 2015 - Vienna Duration: 29 Mar 2015 → 29 Mar 2015

Conference

Conference	2nd Workshop on Bibliometric-Enhanced Information Retrieval, BIR 2015
City	Vienna
Period	29/03/15 → 29/03/15
Other	2nd Workshop on Bibliometric-Enhanced Information Retrieval, BIR 2015 (29/03/2015-29/03/2015, Vienna)

Keywords

polyrepresentative clustering

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title = "Polyrepresentative clustering: a study of simulated user strategies and representations",

abstract = "The principle of polyrepresentation and document clustering are two established methods for Interactive Information Retrieval, which have been used separately so far. In this paper we discuss a cluster based polyrepresentation approach for information need and document based representations. In our work we simulate and evaluate two possible cluster browsing strategies a user could apply to explore the polyrepresentative clusters. In our evaluation we apply information need and bibliographic features on the iSearch collection. Our results suggest that polyrepresentative cluster browsing may be more effective than exploring a ranked list.",

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T1 - Polyrepresentative clustering: a study of simulated user strategies and representations

AU - Abbasi, Muhammad Kamran

AU - Frommholz, Ingo

PY - 2015/12/31

Y1 - 2015/12/31

N2 - The principle of polyrepresentation and document clustering are two established methods for Interactive Information Retrieval, which have been used separately so far. In this paper we discuss a cluster based polyrepresentation approach for information need and document based representations. In our work we simulate and evaluate two possible cluster browsing strategies a user could apply to explore the polyrepresentative clusters. In our evaluation we apply information need and bibliographic features on the iSearch collection. Our results suggest that polyrepresentative cluster browsing may be more effective than exploring a ranked list.

AB - The principle of polyrepresentation and document clustering are two established methods for Interactive Information Retrieval, which have been used separately so far. In this paper we discuss a cluster based polyrepresentation approach for information need and document based representations. In our work we simulate and evaluate two possible cluster browsing strategies a user could apply to explore the polyrepresentative clusters. In our evaluation we apply information need and bibliographic features on the iSearch collection. Our results suggest that polyrepresentative cluster browsing may be more effective than exploring a ranked list.

KW - polyrepresentative clustering

M3 - Conference contribution

VL - 1344

SP - 47

EP - 54

BT - CEUR Workshop Proceedings

PB - CEUR-WS

T2 - 2nd Workshop on Bibliometric-Enhanced Information Retrieval, BIR 2015

Y2 - 29 March 2015 through 29 March 2015

ER -

Polyrepresentative clustering: a study of simulated user strategies and representations

Abstract

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Keywords

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