BioMedLib's relevance score 

3. BioMedLib computes an advanced hybrid relevance score, proprietary to BML, for each article of each query that you submit. By default BioMedLib shows the most relevant articles first, where they have the highest chance to be the "best answers" to your query.
Moreover, you can specify a range of publication dates, within which the articles are then sorted by relevance, thus providing you with both timeliness and relevance.

The factors that are used in computing BioMedLib's relevance score include:

3.1 Semantics: presence of relation in addition to the presence of query words. BioMedLib looks for triplets {Concept1, Relation, Concept2} in each sentence of each article, where Concept1 and Concept2 are from your query. BioMedLib assigns higher relevance score to an article that contains such relation triplets.

3.2 Meaning-based (concept-based) search, besides text-word searching. When you submit a query like 'heart attack', BioMedLib not only searches for the words 'heart' and 'attack', but it also searches for the biomedical concept with ID = C0027051, which is a "Disease or Syndrome", with definition of "gross necrosis of the myocardium, as a result of interruption of the blood supply to the area", which has about 100 synonyms taken from about 150 different vocabularies. Other engines may do similar operation, but they understand only a small fraction of the 2 million concepts that BioMedLib understands. BioMedLib assigns higher relevance score to an article that contains the concept (than an article that contains the query words but in separate and unrelated places).

3.3 BioMedLib's relevance score includes all the factors used in a typical TF-IDF (term frequency - inverse document frequency) operation. For example, field-weighting is one of such features, like when "major" MeSH terms of an article matches your query, versus the minor MeSHes, and that article is given a higher relevance score.

Therefore BioMedLib utilizes an optimized hybrid of multiple scoring systems, some unique to BML, to deliver its superior relevance score.


Read more in the help page.