D-RANK: A FRAMEWORK FOR SCORE AGGREGATION IN SPECIALIZED SEARCH

Martin Veselý, Martin Rajman, Jean-Yves Le Meur, Ludmila Marian, Jérôme Caffaro

2011

Abstract

In this paper we present an approach to score aggregation for specialized search systems. In our work we focus on document ranking in scientific publication databases. We work with the collection of scientific publications of the CERN Document Server. This paper reports on work in progress and describes rank aggregation framework with score normalization. We present results that we obtained with aggregations based on logistic regression using both ranks and scores. In our experiment we concluded that score-based aggregation favored performance in terms of Average Precision and Mean Reciprocal Rank, while rank-based aggregation favored document discovery.

References

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Paper Citation


in Harvard Style

Veselý M., Rajman M., Le Meur J., Marian L. and Caffaro J. (2011). D-RANK: A FRAMEWORK FOR SCORE AGGREGATION IN SPECIALIZED SEARCH . In Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8425-40-9, pages 482-485. DOI: 10.5220/0003293404820485


in Bibtex Style

@conference{icaart11,
author={Martin Veselý and Martin Rajman and Jean-Yves Le Meur and Ludmila Marian and Jérôme Caffaro},
title={D-RANK: A FRAMEWORK FOR SCORE AGGREGATION IN SPECIALIZED SEARCH},
booktitle={Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2011},
pages={482-485},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003293404820485},
isbn={978-989-8425-40-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - D-RANK: A FRAMEWORK FOR SCORE AGGREGATION IN SPECIALIZED SEARCH
SN - 978-989-8425-40-9
AU - Veselý M.
AU - Rajman M.
AU - Le Meur J.
AU - Marian L.
AU - Caffaro J.
PY - 2011
SP - 482
EP - 485
DO - 10.5220/0003293404820485