The LAILAPS Search Engine: Relevance Ranking in Life Science Databases

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...

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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
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spelling doaj-46da28bc98d84ece8732c4e9adc0305e2021-09-06T19:40:30ZengDe GruyterJournal of Integrative Bioinformatics1613-45162010-06-017211110.1515/jib-2010-110biecoll-jib-2010-110The LAILAPS Search Engine: Relevance Ranking in Life Science DatabasesLange Matthias0Spies Karl1Bargsten Joachim2Haberhauer Gregor3Klapperstück Matthias4Leps Michael5Weinel Christian6Wünschiers Röbbe7Weißbach Mandy8Stein Jens9Scholz Uwe10Research Group Bioinformatics and Information Technology, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, GermanyResearch Group Bioinformatics and Information Technology, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, GermanyResearch Group Bioinformatics and Information Technology, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, GermanyBASF SE, Computational Chemistry and Biology, Ludwigshafen, GermanyResearch Group Bioinformatics and Information Technology, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, GermanySunGene GmbH, Gatersleben, GermanyBASF SE, Computational Chemistry and Biology, Ludwigshafen, GermanyUniversity of Applied Sciences, Mittweida, GermanyResearch Group Bioinformatics and Information Technology, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, GermanySunGene GmbH, Gatersleben, GermanyResearch Group Bioinformatics and Information Technology, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, GermanySearch 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, we present the LAILAPS search engine for life science databases. The concept is to combine a novel feature model for relevance ranking, a machine learning approach to model user relevance profiles, ranking improvement by user feedback tracking and an intuitive and slim web user interface, that estimates relevance rank by tracking user interactions. Queries are formulated as simple keyword lists and will be expanded by synonyms. Supporting a flexible text index and a simple data import format, LAILAPS can easily be used both as search engine for comprehensive integrated life science databases and for small in-house project databases.https://doi.org/10.1515/jib-2010-110
collection DOAJ
language English
format Article
sources DOAJ
author Lange Matthias
Spies Karl
Bargsten Joachim
Haberhauer Gregor
Klapperstück Matthias
Leps Michael
Weinel Christian
Wünschiers Röbbe
Weißbach Mandy
Stein Jens
Scholz Uwe
spellingShingle Lange Matthias
Spies Karl
Bargsten Joachim
Haberhauer Gregor
Klapperstück Matthias
Leps Michael
Weinel Christian
Wünschiers Röbbe
Weißbach Mandy
Stein Jens
Scholz Uwe
The LAILAPS Search Engine: Relevance Ranking in Life Science Databases
Journal of Integrative Bioinformatics
author_facet Lange Matthias
Spies Karl
Bargsten Joachim
Haberhauer Gregor
Klapperstück Matthias
Leps Michael
Weinel Christian
Wünschiers Röbbe
Weißbach Mandy
Stein Jens
Scholz Uwe
author_sort Lange Matthias
title The LAILAPS Search Engine: Relevance Ranking in Life Science Databases
title_short The LAILAPS Search Engine: Relevance Ranking in Life Science Databases
title_full The LAILAPS Search Engine: Relevance Ranking in Life Science Databases
title_fullStr The LAILAPS Search Engine: Relevance Ranking in Life Science Databases
title_full_unstemmed The LAILAPS Search Engine: Relevance Ranking in Life Science Databases
title_sort lailaps search engine: relevance ranking in life science databases
publisher De Gruyter
series Journal of Integrative Bioinformatics
issn 1613-4516
publishDate 2010-06-01
description 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, we present the LAILAPS search engine for life science databases. The concept is to combine a novel feature model for relevance ranking, a machine learning approach to model user relevance profiles, ranking improvement by user feedback tracking and an intuitive and slim web user interface, that estimates relevance rank by tracking user interactions. Queries are formulated as simple keyword lists and will be expanded by synonyms. Supporting a flexible text index and a simple data import format, LAILAPS can easily be used both as search engine for comprehensive integrated life science databases and for small in-house project databases.
url https://doi.org/10.1515/jib-2010-110
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