PubMed related articles: a probabilistic topic-based model for content similarity

By Bmc Bioinformatics, Jimmy J. Lin, J. Wilbur, John Wilbur, Email. 2007

276 citations recorded by the source corpus.

BackgroundWe present a probabilistic topic-based model for content similarity called pmra that underlies the related article search feature in PubMed. Whether or not a document is about a particular topic is computed from term frequencies, modeled as Poisson distributions. Unlike previous probabilistic retrieval models, we do not attempt to estimate relevance–but rather our focus is "relatedness", the probability that a user would want to examine a particular document given known interest in another. We also describe a novel technique for estimating parameters that does not require human relevance judgments; instead, the process is based on the existence of MeSH ® in MEDLINE ®.ResultsThe pmra retrieval model was compared against bm25, a competitive probabilistic model that shares theoretical similarities. Experiments using the test collection from the TREC 2005 genomics track shows a small but statistically significant improvement of pmra over bm25 in terms of precision.ConclusionOur experiments suggest that the pmra model provides an effective ranking algorithm for related article search.

Subfields: General Health Professions, Information Systems, Molecular Biology

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Citations in the corpus

BioCreative V CDR task corpus: a resource for chemical disease relation extraction (2016, methodology): “For each new article, we computed an overall score by summing the similarity scores (20,21) between the target article and each article in the training and development sets.”
Research-paper recommender systems: a literature survey (2015, unknown): “The approaches extracted words from the title [79,85, 112], abstract [26,51,61], header [43], introduction [57], foreword [57], author-provided keywords [26,57,58], and bibliography [27], as well as from the papers’ body text [65,101,112].”
Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Health (2023, background): “Information retrieval (IR) is an integral part in clinical decision making [47] and biomedical knowledge acquisition [48], as it covers various information-seeking behaviors such as literature search [49], question answering [50], and article recommendation [51].”
PRISMA-S: an extension to the PRISMA statement for reporting literature searches in systematic reviews (2021, methodology): “Another is using databases’ built in tools, such as PubMed’s Related Articles feature [86] or Clarivate Analytics’ Web of Science’s Related Records feature [87], to locate relevant articles based on commonalities with a starting article.”