Authors:
Nedra Ibrahim
;
Anja Habacha Chaibi
and
Henda Ben Ghézala
Affiliation:
RIADI Laboratory and ENSI, Tunisia
Keyword(s):
Scientometric Indicators, Qualitative Search, Scientometric Annotation, Re-ranking, Similarity Score, User Profile, User Model.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Data Engineering
;
Enterprise Information Systems
;
HCI on Enterprise Information Systems
;
Health Information Systems
;
Human Factors
;
Human-Computer Interaction
;
Information Systems Analysis and Specification
;
Knowledge Management
;
Ontologies and the Semantic Web
;
Physiological Computing Systems
;
Society, e-Business and e-Government
;
Web Information Systems and Technologies
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 th
e existence of correlation between research paper quality and paper relevance. The revelation of this correlation implies better retrieval performance.
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