Benchmarking Domain-Specific Expert Search Using Workshop Program Committees

Peter Paul Buitelaar

doi:http://hdl.handle.net/10379/4131

Benchmarking Domain-Specific Expert Search Using Workshop Program Committees

Peter Paul Buitelaar

Research output: Chapter in Book or Conference Publication/Proceeding › Conference Publication › peer-review

Abstract

Traditionally, relevance assessments for expert search have been gathered through self-assessment or based on the opinions of co-workers. We introduce three benchmark datasets1 for expert search that use conference workshops for relevance assessment. Our data sets cover entire research domains as opposed to single institutions. In addition, they provide a larger number of topic-person associations and allow a more objective and fine-grained evaluation of expertise than existing data sets do. We present and discuss baseline results for a language modelling and a topic-centric approach to expert search. We find that the topic-centric approach achieves the best results on domain-specific datasets.

Original language	English (Ireland)
Title of host publication	Proceedings of the workshop on Computational Scientometrics: Theory and Applications, at the 22nd ACM International Conference on Information and Knowledge Management (CIKM 2013)
DOIs	https://doi.org/http://hdl.handle.net/10379/4131
Publication status	Published - 1 Jan 2013

Authors (Note for portal: view the doc link for the full list of authors)

Authors
Georgeta Bordea, Toine Bogers and Paul Buitelaar

Access to Document

http://hdl.handle.net/10379/4131

Cite this

@inproceedings{43e8cce4a4fd48d1bb383ae2d35ae361,

title = "Benchmarking Domain-Specific Expert Search Using Workshop Program Committees",

abstract = "Traditionally, relevance assessments for expert search have been gathered through self-assessment or based on the opinions of co-workers. We introduce three benchmark datasets1 for expert search that use conference workshops for relevance assessment. Our data sets cover entire research domains as opposed to single institutions. In addition, they provide a larger number of topic-person associations and allow a more objective and fine-grained evaluation of expertise than existing data sets do. We present and discuss baseline results for a language modelling and a topic-centric approach to expert search. We find that the topic-centric approach achieves the best results on domain-specific datasets. ",

author = "Buitelaar, \{Peter Paul\}",

year = "2013",

month = jan,

day = "1",

doi = "http://hdl.handle.net/10379/4131",

language = "English (Ireland)",

booktitle = "Proceedings of the workshop on Computational Scientometrics: Theory and Applications, at the 22nd ACM International Conference on Information and Knowledge Management (CIKM 2013)",

}

Benchmarking Domain-Specific Expert Search Using Workshop Program Committees. / Buitelaar, Peter Paul.
Proceedings of the workshop on Computational Scientometrics: Theory and Applications, at the 22nd ACM International Conference on Information and Knowledge Management (CIKM 2013). 2013.

Research output: Chapter in Book or Conference Publication/Proceeding › Conference Publication › peer-review

TY - GEN

T1 - Benchmarking Domain-Specific Expert Search Using Workshop Program Committees

AU - Buitelaar, Peter Paul

PY - 2013/1/1

Y1 - 2013/1/1

N2 - Traditionally, relevance assessments for expert search have been gathered through self-assessment or based on the opinions of co-workers. We introduce three benchmark datasets1 for expert search that use conference workshops for relevance assessment. Our data sets cover entire research domains as opposed to single institutions. In addition, they provide a larger number of topic-person associations and allow a more objective and fine-grained evaluation of expertise than existing data sets do. We present and discuss baseline results for a language modelling and a topic-centric approach to expert search. We find that the topic-centric approach achieves the best results on domain-specific datasets.

AB - Traditionally, relevance assessments for expert search have been gathered through self-assessment or based on the opinions of co-workers. We introduce three benchmark datasets1 for expert search that use conference workshops for relevance assessment. Our data sets cover entire research domains as opposed to single institutions. In addition, they provide a larger number of topic-person associations and allow a more objective and fine-grained evaluation of expertise than existing data sets do. We present and discuss baseline results for a language modelling and a topic-centric approach to expert search. We find that the topic-centric approach achieves the best results on domain-specific datasets.

U2 - http://hdl.handle.net/10379/4131

DO - http://hdl.handle.net/10379/4131

M3 - Conference Publication

BT - Proceedings of the workshop on Computational Scientometrics: Theory and Applications, at the 22nd ACM International Conference on Information and Knowledge Management (CIKM 2013)

ER -

Benchmarking Domain-Specific Expert Search Using Workshop Program Committees

Abstract

Authors (Note for portal: view the doc link for the full list of authors)

Access to Document

Fingerprint

Cite this