Abstract: The query suggestion API enables a real-time, semantic query suggestion for keyword based query systems. It has been implemented as RESTful service and can easily be integrated into third-party applications. Compared to popular search frameworks, like Apache Lucene, the suggested queries consider biological background knowledge that was extracted from biomedical literature. The service was successfully applied in the LAILAPS plant science search engine. In particular we were able to discover inferred associations between traits and genes and use them to automatically reformulate search phrases. The training dataset consits of 13,930,050 documents from PubMed articles, and gene and protein function describtions from UniProt, Plant Ontology and Gene Ontology.
License: CC BY 4.0 (Creative Commons Attribution)
DOI: 10.5447/ipk/2016/2
Content: 1 Directories 2 Files (4 GB)
| CONTRIBUTOR: |
Matthias Lange
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| CREATOR: |
Jinbo Chen
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| PUBLISHER: | e!DAL - Plant Genomics and Phenomics Research Data Repository (PGP), IPK Gatersleben, Seeland OT Gatersleben, Corrensstraße 3, 06466, Germany |
| SIZE: | 4 GB |
| SUBJECT: | Information Retrieval in Life Sciences, Query Suggestion, Big Data Mining |