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Authors: Nedra Ibrahim ; Anja Habacha Chaibi and Henda Ben Ghézala

Affiliation: RIADI Laboratory and ENSI, Tunisia

ISBN: 978-989-758-298-1

Keyword(s): Scientometric Indicators, Qualitative Search, Scientometric Annotation, Re-ranking, Similarity Score, User Profile, User Model.

Abstract: Scientific researchers are a special kind of users which know their objective. One of the challenges facing todays’ researchers is how to find qualitative information that meets their needs. One potential method for assisting scientific researcher is to employ a personalized definition of quality to focus information search results. Scientific quality is measured by the mean of a set of scientometric indicators. This paper presents a personalized information retrieval approach based on scientometric indicators. The proposed approach includes a scientometric document annotator, a scientometric user model, a scientometric retrieval model and a scientometric ranking method. We discuss the feasibility of this approach by performing different experimentations on its different parts. The incorporation of scientometric indicators into the different parts of our approach has significantly improved retrieval performance which is rated for 41.66%. An important implication of this finding is the existence of correlation between research paper quality and paper relevance. The revelation of this correlation implies better retrieval performance. (More)

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Paper citation in several formats:
Ibrahim N., Chaibi A. and Ghézala H. (2018). A Scientometric Approach for Personalizing Research Paper Retrieval.In Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-298-1, pages 419-428. DOI: 10.5220/0006671204190428

@conference{iceis18,
author={Nedra Ibrahim and Anja Habacha Chaibi and Henda Ben Ghézala},
title={A Scientometric Approach for Personalizing Research Paper Retrieval},
booktitle={Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2018},
pages={419-428},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006671204190428},
isbn={978-989-758-298-1},
}

TY - CONF

JO - Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - A Scientometric Approach for Personalizing Research Paper Retrieval
SN - 978-989-758-298-1
AU - Ibrahim N.
AU - Chaibi A.
AU - Ghézala H.
PY - 2018
SP - 419
EP - 428
DO - 10.5220/0006671204190428

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