Exploiting information needs and bibliographics for polyrepresentative document clustering

Ingo Frommholz; Muhammad Kamran Abbasi

Exploiting information needs and bibliographics for polyrepresentative document clustering

Ingo Frommholz
, Muhammad Kamran Abbasi

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

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Abstract

In this paper we explore the potential of combining the principle of polyrepresentation with document clustering. Our idea is discussed and evaluated for polyrepresentation of information needs as wells as for document-based polyrepresentation where bibliographic information is used as representation. The main idea is to present the user with the highly ranked polyrepresentative clusters to support the search process. Our evaluation suggests that our approach is capable of increasing retrieval performance, but performance varies for queries with a high or low number of relevant documents.

Original language	English
Title of host publication	BIR 2014 Bibliometric-enhanced Information Retrieval
Publisher	CEUR-WS
Publication status	Published - 10 Apr 2014
Event	BIR 2014 Bibliometric-enhanced Information Retrieval - Amsterdam Duration: 13 Apr 2014 → 13 Apr 2014

Conference

Conference	BIR 2014 Bibliometric-enhanced Information Retrieval
City	Amsterdam
Period	13/04/14 → 13/04/14
Other	BIR 2014 Bibliometric-enhanced Information Retrieval (13/04/2014-13/04/2014, Amsterdam)

Keywords

information retrieval

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Paper3Accepted author manuscript, 720 KBLicence: CC BY-NC-ND

http://ceur-ws.org/Vol-1143/

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title = "Exploiting information needs and bibliographics for polyrepresentative document clustering",

abstract = "In this paper we explore the potential of combining the principle of polyrepresentation with document clustering. Our idea is discussed and evaluated for polyrepresentation of information needs as wells as for document-based polyrepresentation where bibliographic information is used as representation. The main idea is to present the user with the highly ranked polyrepresentative clusters to support the search process. Our evaluation suggests that our approach is capable of increasing retrieval performance, but performance varies for queries with a high or low number of relevant documents.",

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author = "Ingo Frommholz and Abbasi, \{Muhammad Kamran\}",

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language = "English",

booktitle = "BIR 2014 Bibliometric-enhanced Information Retrieval",

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T1 - Exploiting information needs and bibliographics for polyrepresentative document clustering

AU - Frommholz, Ingo

AU - Abbasi, Muhammad Kamran

PY - 2014/4/10

Y1 - 2014/4/10

N2 - In this paper we explore the potential of combining the principle of polyrepresentation with document clustering. Our idea is discussed and evaluated for polyrepresentation of information needs as wells as for document-based polyrepresentation where bibliographic information is used as representation. The main idea is to present the user with the highly ranked polyrepresentative clusters to support the search process. Our evaluation suggests that our approach is capable of increasing retrieval performance, but performance varies for queries with a high or low number of relevant documents.

AB - In this paper we explore the potential of combining the principle of polyrepresentation with document clustering. Our idea is discussed and evaluated for polyrepresentation of information needs as wells as for document-based polyrepresentation where bibliographic information is used as representation. The main idea is to present the user with the highly ranked polyrepresentative clusters to support the search process. Our evaluation suggests that our approach is capable of increasing retrieval performance, but performance varies for queries with a high or low number of relevant documents.

KW - information retrieval

M3 - Conference contribution

BT - BIR 2014 Bibliometric-enhanced Information Retrieval

PB - CEUR-WS

T2 - BIR 2014 Bibliometric-enhanced Information Retrieval

Y2 - 13 April 2014 through 13 April 2014

ER -

Exploiting information needs and bibliographics for polyrepresentative document clustering

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Conference

Keywords

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