Evaluating Different Ranking Functions for Context-Based Literature Search

Ratprasartporn, Nattakarn; Bani‐Ahmad, Sulieman; Çakmak, Ali; Po, Jonathan; Özsoyoǧlu, Gültekin

doi:10.1109/icdew.2007.4401002

Cited by 4 publications

(1 citation statement)

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“…In this paper [7], the authors present three different prestige score (ranking) functions for the contextbased environment, namely, citation-based, text-based, and pattern-based score functions. Using biomedical publications as the test case and Gene Ontology as the context hierarchy, the authors have evaluated the proposed ranking functions in terms of their accuracy and separability.…”

Section: State-of-the-artmentioning

confidence: 99%

Ranking MEDLINE documents

2014

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Background: BioTextRetriever is a Web-based search tool for retrieving relevant literature in Molecular Biology and related domains from MEDLINE. The core of BioTextRetriever is the dynamic construction of a classifier capable of selecting relevant papers among the whole MEDLINE bibliographic database. "Relevant" papers, in this context, means papers related to a set of DNA or protein sequences provided as input to the tool by the user. Methods: Since the number of retrieved papers may be very large, BioTextRetriever uses a novel ranking algorithm to retrieve the most relevant papers first. We have developed a new methodology that enables the automation of the assessment process based on a multi-criteria ranking function. This function combines six factors: MeSH terms, paper's number of citations, author's h-index, journals impact factor, author number of publications and journal similarity function. Results:The best results highlight the number of citations and the h-index factors. Conclusions:We have developed and a multi-criteria ranking function, that contemplates six factors, and that seems appropriate to retrieve relevant papers out of a huge repository such as MEDLINE.

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Section: State-of-the-artmentioning

confidence: 99%