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Article

Broad expertise retrieval in sparse data environments

Authors:

Krisztian Balog,

Leif Azzopardi,

Maarten de Rijke,

Antal van den BoschAuthors Info & Claims

SIGIR '07: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval

Pages 551 - 558

https://doi.org/10.1145/1277741.1277836

Published: 23 July 2007 Publication History

Abstract

Expertise retrieval has been largely unexplored on data other than the W3C collection. At the same time, many intranets of universities and other knowledge-intensive organisations offer examples of relatively small but clean multilingual expertise data, covering broad ranges of expertise areas. We first present two main expertise retrieval tasks, along with a set of baseline approaches based on generative language modeling, aimed at finding expertise relations between topics and people. For our experimental evaluation, we introduce (and release) a new test set based on a crawl of a university site. Using this test set, we conduct two series of experiments. The first is aimed at determining the effectiveness of baseline expertise retrieval methods applied to the new test set. The second is aimed at assessing refined models that exploit characteristic features of the new test set, such as the organizational structure of the university, and the hierarchical structure of the topics in the test set. Expertise retrieval models are shown to be robust with respect to environments smaller than the W3C collection, and current techniques appear to be generalizable to other settings.

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Index Terms

Broad expertise retrieval in sparse data environments
1. Information systems

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Information & Contributors

Information

Published In

cover image ACM Conferences

SIGIR '07: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval

July 2007

946 pages

ISBN:9781595935977

DOI:10.1145/1277741

General Chairs:
Wessel Kraaij
TNO, The Netherlands
,
Arjen P. de Vries
CWI, The Netherlands
,
Program Chairs:
Charles L. A. Clarke
University of Waterloo, Canada
,
Norbert Fuhr
University of Duisburg-Essen, Germany
,
Noriko Kando
National Institute of Informatics, Japan

Copyright © 2007 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 23 July 2007

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SIGIR07: The 30th Annual International SIGIR Conference

July 23 - 27, 2007

Amsterdam, The Netherlands

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Overall Acceptance Rate 792 of 3,983 submissions, 20%

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https://dl.acm.org/doi/10.1145/3571306.3571372
Vo DTran TShirai KHuynh V(2022)Deep Generative Networks Coupled With Evidential Reasoning for Dynamic User Preferences Using Short TextsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.3188497(1-16)Online publication date: 2022
https://doi.org/10.1109/TKDE.2022.3188497
de Sousa SDias TPinto A(2022)A Strategy for Identifying Specialists in Scientific Data RepositoriesMobile Networks and Applications10.1007/s11036-022-01964-027:5(1941-1951)Online publication date: 3-May-2022
https://doi.org/10.1007/s11036-022-01964-0
Nardini FTrani RVenturini R(2021)Fast Filtering of Search Results Sorted by AttributeACM Transactions on Information Systems10.1145/347798240:2(1-24)Online publication date: 24-Nov-2021
https://dl.acm.org/doi/10.1145/3477982
Pan YLiang SRen JMeng ZZhang Q(2021)Personalized, Sequential, Attentive, Metric-Aware Product SearchACM Transactions on Information Systems10.1145/347333740:2(1-29)Online publication date: 24-Nov-2021
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Liang SLuo YMeng Z(2021)Profiling Users for Question Answering Communities via Flow-Based Constrained Co-Embedding ModelACM Transactions on Information Systems10.1145/347056540:2(1-38)Online publication date: 24-Nov-2021
https://dl.acm.org/doi/10.1145/3470565
Sousa SDias TPinto A(2021)Neural Weak Supervision Model for Search of Specialists in Scientific Data RepositoryData and Information in Online Environments10.1007/978-3-030-77417-2_21(286-296)Online publication date: 15-Jun-2021
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Bukowski MGeisler SSchmitz-Rode TFarkas R(2020)Feasibility of activity-based expert profiling using text mining of scientific publications and patentsScientometrics10.1007/s11192-020-03414-8Online publication date: 18-Mar-2020
https://doi.org/10.1007/s11192-020-03414-8
Vo DHoang AHuynh V(2020)An Evidential Reasoning Framework for User Profiling Using Short TextsIntegrated Uncertainty in Knowledge Modelling and Decision Making10.1007/978-3-030-62509-2_12(137-150)Online publication date: 2-Nov-2020
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Angelova MManasa Devagiri VBoeva VLinde PLavesson N(2019)An Expertise Recommender System based on Data from an Institutional Repository (DiVA)Connecting the Knowledge Commons — From Projects to Sustainable Infrastructure10.4000/books.oep.9078(135-149)Online publication date: 2-Jun-2019
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