TY  - JOUR
A1  - Lange, Matthias
A1  - Spies, Karl
A1  - Colmsee, Christian
A1  - Flemming, Steffen
A1  - Klapperstück, Matthias
A1  - Scholz, Uwe
T1  - The LAILAPS search engine: a feature model for relevance ranking in life science databases.
JO  - Journal of integrative bioinformatics
Y1  - 2010/12/31
VL  - 7
IS  - 3
SN  - 1613-4516
AD  - Bioinformatics and Information Technology, Leibniz Institute of Plant Genetics and Crop Plant Research, Corrensstrasse 3, 06466 Gatersleben, Germany.lange@ipk-gatersleben.de
N2  - Efficient and effective information retrieval in life sciences is one of the most pressing challenge in bioinformatics. . The incredible growth of life science databases to a vast network of interconnected information systems is to the same extent a big challenge and a great chance for life science research. . The knowledge found in the Web, in particular in life-science databases, are a valuable major resource. . In order to bring it to the scientist desktop, it is essential to have well performing search engines. . Thereby, not the response time nor the number of results is important. . The most crucial factor for millions of query results is the relevance ranking. . In this paper, we present a feature model for relevance ranking in life science databases and its implementation in the LAILAPS search engine. . Motivated by the observation of user behavior during their inspection of search engine result, we condensed a set of 9 relevance discriminating features. . These features are intuitively used by scientists, who briefly screen database entries for potential relevance. . The features are both sufficient to estimate the potential relevance, and efficiently quantifiable. . The derivation of a relevance prediction function that computes the relevance from this features constitutes a regression problem. . To solve this problem, we used artificial neural networks that have been trained with a reference set of relevant database entries for 19 protein queries. . Supporting a flexible text index and a simple data import format, this concepts are implemented in the LAILAPS search engine. . It can easily be used both as search engine for comprehensive integrated life science databases and for small in-house project databases. . LAILAPS is publicly available for SWISSPROT data at http://lailaps.ipk-gatersleben.de.
ID  - 20375444.001
ER  -