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Differentiating features of BioMedLibHere we explain why BioMedLib™ provides better search results than other search engines. This is in-depth reading.
BioMedLib provides "meaning-based search" in addition to the widely available "keyword search".
In a keyword search, the search engine looks for occurrence of user's words in each document, literally. For example if user submits the query 'coronary attack' the keyword search will return results that are often dramatically different than when user submits the query 'heart attack' .
In the meaning-based search, the search engine is aware that both queries 'heart attack' and 'coronary attack' point to the same meaning (the same UMLS concept with ID of C0027051). Therefore the BioMedLib search engine will find not only documents that match literally to user's query words, but also will find all other documents that express the same meaning by using "synonyms" of user's words. This guaranties the user won't miss relevant documents just because of the variation in the words the user used to express the question.
BioMedLib provides "semantic search", on top of the meaning-based search (which in turn is added on top of keyword search).
When you submit a multiword query, of course you like to see documents that contain those words. Besides, the document should have the query words in a "related" fashion.
For example if you submit 'plastic surgery infection' , then not only the documents should contain the three words, but also the documents should explain a sort of relationships between the words. You don't want a document that talks about infection in one paragraph, and talks about plastic surgery somewhere else and unrelated to the infection; do you?
BioMedLib makes sure documents that express relationship between the concepts of your query, will get higher ranks, so that you find them at the top of the first page of results.
Better keyword search
BioMedLib, besides its meaning-based search, provides a more accurate keyword search as well.
For example submit the double-quoted query "single dose erythromycin" to PubMed, and PubMed will tell you that there is no article in the MEDLINE having the exact phrase "single dose erythromycin". This is not true; in other words PubMed is missing articles that have the exact phrase "single dose erythromycin". Try it with BioMedLib , and you will see articles with PubMed IDs 7081971 and 3335066 actually have the exact phrase.
[Kroboth PD, Brown A, Lyon JA, Kroboth FJ, Juhl RP. Pharmacokinetics of single-dose erythromycin in normal and alcoholic liver disease subjects. Antimicrob Agents Chemother. 1982 Jan;21(1):135-40. PMID: 7081971.]
[Malinverni R, Overholser CD, Bille J, Glauser MP. Antibiotic prophylaxis of experimental endocarditis after dental extractions. Circulation. 1988 Jan;77(1):182-7. PMID: 3335066.]
You can try the IDs 7081971 and 3335066 in PubMed and see that the two articles do exist in PubMed's backend database, but PubMed is unable to find them in response to the exact phrase query "single dose erythromycin" (as of November 2009; and August 2010).
Hassle-free advanced search
The advantages of BioMedLib's meaning-based search and semantic search come with zero extra hassle for the user. You enter your query as usual, and BioMedLib engine will expand and optimize your query automatically, no questions asked.
And if you don't like the idea, just uncheck the "expand the query" box in the "[+] Query is expanded" area; and you will get a simple keyword search!
(Note: sometimes the "[+] Query is expanded" area is denoted as "[+] Clarify the query")
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© 2019 BioMedLib
© 2019 BioMedLib