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Information retrieval from scientific abstract and citation databases: A query-by-documents approach based on Monte-Carlo sampling

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10.1016/j.eswa.2022.116967
 
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hdl:2117/370214

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Lechtenberg, FabianMés informacióMés informació
Farreres de la Morena, XavierMés informacióMés informacióMés informació
Galvan Cara, Aldwin Lois
Somoza Tornos, AnaMés informacióMés informació
Espuña Camarasa, AntonioMés informacióMés informacióMés informació
Graells Sobré, MoisèsMés informacióMés informacióMés informació
Document typeArticle
Defense date2022-08-01
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 4.0 International
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 4.0 International
Abstract
The rapidly increasing amount of information and entries in abstract and citation databases steadily complicates the information retrieval task. In this study, a novel query-by-document approach using Monte-Carlo sampling of relevant keywords is presented. From a set of input documents (seed) keywords are extracted using TF-IDF and subsequently sampled to repeatedly construct queries to the database. The occurrence of returned documents is counted and serves as a proxy relevance metric. Two case studies based on the Scopus® database are used to demonstrate the method and its key advantages. No expert knowledge and human intervention is needed to construct the final search strings which reduces the human bias. The methods practicality is supported by the high re-retrieval of seed documents of 7/8 and 26/31 in high ranks in the two presented case studies.
CitationLechtenberg, F. [et al.]. Information retrieval from scientific abstract and citation databases: A query-by-documents approach based on Monte-Carlo sampling. "Expert systems with applications", 1 Agost 2022, vol. 199, núm. 116967. 
URIhttp://hdl.handle.net/2117/370214
DOI10.1016/j.eswa.2022.116967
ISSN0957-4174
Publisher versionhttps://www.sciencedirect.com/science/article/pii/S0957417422003931
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