01738nas a2200157   4500008004100000245007800041210006900119260001200188300001000200490000700210520124700217100001901464700002601483700002401509856004701533       2021                        eng d00a Incorporating Quality Measurement into Scientific Document Retrieval –0 aIncorporating Quality Measurement into Scientific Document Retri  c06/2021  a47-580 v193 a<p><span style="color: rgb(51, 51, 51); font-family: Arial, Helvetica, sans-serif;">&nbsp;One of the challenges facing today's researchers is how to find qualitative information that meets their needs. In scientific research, the quality of information is very important for institution quality improvement and research validation. The main purpose of the paper is the proposal of a scientometric annotation approach to improve retrieval system performance and meet researchersâ€™ needs. In this work, we discuss how to use scientometrics in document annotation to improve information quality. One possible solution to this problem is to automate and facilitate the selection of qualitative scientific documents by enriching the document annotation process with scientometric criterion. Our approach provided better performance for retrieval system compared to BM25 retrieval model. The best performance was supplied by the integration of document citation number and journal or conference ranking. The best improvement rate was 34.21% in F-measure, 52.22% in nDCG, 27.45% in MAP and 83.33% in P(k). An important implication of this finding is the existence of correlation between research paper quality and paper relevance.</span></p>
1 aIbrahim, Nedra1 aChaibi, Anja, Habacha1 aBen Ghézala, Henda  uhttp://www.dline.info/download.php?sn=3259