The LAILAPS Search Engine: Relevance Ranking in Life Science Databases
Search engines and retrieval systems are popular tools at a life science desktop. The manual inspection of hundreds of database entries, that reflect a life science concept or fact, is a time intensive daily work. Hereby, not the number of query results matters, but the relevance does. In this paper...
Main Authors: | Lange Matthias, Spies Karl, Bargsten Joachim, Haberhauer Gregor, Klapperstück Matthias, Leps Michael, Weinel Christian, Wünschiers Röbbe, Weißbach Mandy, Stein Jens, Scholz Uwe |
---|---|
Format: | Article |
Language: | English |
Published: |
De Gruyter
2010-06-01
|
Series: | Journal of Integrative Bioinformatics |
Online Access: | https://doi.org/10.1515/jib-2010-110 |
Similar Items
-
The LAILAPS Search Engine: A Feature Model for Relevance Ranking in Life Science Databases
by: Lange Matthias, et al.
Published: (2010-12-01) -
LAILAPS-QSM: A RESTful API and JAVA library for semantic query suggestions.
by: Jinbo Chen, et al.
Published: (2018-03-01) -
A case study for efficient management of high throughput primary lab data
by: Lange Matthias, et al.
Published: (2011-10-01) -
IDPredictor: predict database links in biomedical database
by: Mehlhorn Hendrik, et al.
Published: (2012-06-01) -
Data Linkage Graph: computation, querying and knowledge discovery of life science database networks
by: Lange Matthias, et al.
Published: (2007-12-01)