XplorMed: a tool for exploring MEDLINE abstracts

doi:10.1016/S0968-0004(01)01926-0

Trends in Biochemical Sciences

Volume 26, Issue 9, 1 September 2001, Pages 573-575

https://doi.org/10.1016/S0968-0004(01)01926-0 Get rights and content

Abstract

The most frequent access to the MEDLINE database of scientific abstracts is by keyword search. However, this is often not sufficient because although the user might find all the useful abstracts, these are buried in hundreds that are irrelevant. The exploratory tool XplorMed has been developed to analyse the result of any MEDLINE query. It suggests main groups of related topics and documents, sparing the user the need of reading all abstracts.

Section snippets

Current limitations

The MEDLINE public servers already allow primary forms of document retrieval, the most popular of which is the selection of entries by the presence of a word or series of words (that can be combined by logical rules) in the titles, abstracts or MeSH terms (controlled set of keywords manually assigned by the compilers of MEDLINE, http://www.nlm.nih.gov/mesh/meshhome.html). Such ‘hard’ selection rules are not optimal for IR of documents written by humans (in natural language) ². Obviously, making

Analysis with XplorMed

To aid the kind of manual analysis that one would need in the cases described above, we have developed a system (XplorMed, http://www.bork.embl-heidelberg.de/xplormed/) that provides an intermediate level of analysis (Fig. 1). The system starts with the results of a query in MEDLINE (Fig. 1a). The relations between words (nouns) present in the same abstract are described using two fuzzy binary relations ³ that are more suitable for the modelling of natural language relationships than other

Acknowledgements

Thanks to our group members for fruitful discussions, to Alberto Pascual (CNB, Madrid) for useful insights, and to the developers and maintainers of the MEDLINE database. A publicly available standard grammatical tagger (TreeTagger, from Helmut Schmid of the Institut für Maschinelle Sprachverarbeitung, Stuttgart University, http://www.ims.uni-stuttgart.de/projekte/corplex/TreeTagger/DecisionTreeTagger.html) was used for sentence boundary detection, word stemming, word lemmatization and

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Trends in Biochemical Sciences

ForumXplorMed: a tool for exploring MEDLINE abstracts

Abstract

Section snippets

Current limitations

Analysis with XplorMed

Acknowledgements

FEBS Lett.

Comput. Biol. Med.

Trends Biochem. Sci.

Trends Biochem. Sci.

Trends Biochem. Sci.

Trends Biochem. Sci.

Forum
XplorMed: a tool for exploring MEDLINE abstracts