Scientometric re-ranking approach to improve search results | Zendy

Nedra Ibrahim | Zendy; Anja Habacha Chaïbi | Zendy; Henda Ben Ghézala | Zendy

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Scientometric re-ranking approach to improve search results

Author(s) -

Nedra Ibrahim,

Anja Habacha Chaïbi,

Henda Ben Ghézala

Publication year - 2017

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2017.08.020

Subject(s) - ranking (information retrieval) , computer science , information retrieval , personalization , originality , scientometrics , focus (optics) , quality (philosophy) , journal ranking , data science , world wide web , citation , qualitative research , social science , philosophy , physics , epistemology , sociology , optics

Common personalization approaches involve re-ranking search results. In such way, documents likely to be preferred by the user are presented higher. In this paper, we focus on research-paper retrieval. We propose a scientometric re-ranking approach based on the scientometric preferences of a particular researcher. The researcher creates its own definition of document quality by the mean of scientometric indicators. These indicators are the base of the scientometric score calculation, which serves to results re-ranking. The originality of our approach was the incorporation of different scientometric indicators into researcher’s preferences which have significantly improved ranking performance.

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