PUBSEARCH - A Hierarchical Heuristic Scheme for Ranking Academic Search Results

Emmanouil Amolochitis, Ioannis T. Christou, Zheng-Hua Tan

Abstract

In this paper we present PubSearch, a meta-search engine system for academic publications. We have designed a ranking algorithm consisting of a hierarchical set of heuristic models including term frequency, depreciated citation count and a graph-based score for associations among paper index terms. We used our algorithm to re-rank the default search results produced by online digital libraries such as ACM Portal in response to specific user-submitted queries. The experimental results show that the ranking algorithm used by our system can provide a more relevant ranking scheme compared to ACM Portal.

References

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Paper Citation


in Harvard Style

Amolochitis E., T. Christou I. and Tan Z. (2012). PUBSEARCH - A Hierarchical Heuristic Scheme for Ranking Academic Search Results . In Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM, ISBN 978-989-8425-99-7, pages 509-514. DOI: 10.5220/0003704705090514


in Bibtex Style

@conference{icpram12,
author={Emmanouil Amolochitis and Ioannis T. Christou and Zheng-Hua Tan},
title={PUBSEARCH - A Hierarchical Heuristic Scheme for Ranking Academic Search Results},
booktitle={Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,},
year={2012},
pages={509-514},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003704705090514},
isbn={978-989-8425-99-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,
TI - PUBSEARCH - A Hierarchical Heuristic Scheme for Ranking Academic Search Results
SN - 978-989-8425-99-7
AU - Amolochitis E.
AU - T. Christou I.
AU - Tan Z.
PY - 2012
SP - 509
EP - 514
DO - 10.5220/0003704705090514