Using Maximum Entropy Model for Concept-Based Genomic Information Retrieval

Author

Jiang, TengFei ; He, Tingting ; Tu, Xinhui ; Zhang, Maoyuan

Author_Institution

Dept. of Comput. Sci., HuaZhong Normal Univ., Wuhan, China

fYear

2010

fDate

23-25 April 2010

Firstpage

1

Lastpage

4

Abstract

Genomic Information Retrieval which contains huge highly specific information causes many problems, such as the synonym problem, long term name and rapid growing literature size. In this paper, we use a concept-based model for indexing and querying, which is not like the translation model or the traditional query expansion techniques. We adopt an extraction tool, MaxMatcher, which using Universal Medical Language System (UMLS) concepts to extract the concepts. After extracting concepts, there are some words or phrases would have two or more concept IDs. So, we use Maximum Entropy model to calculate the ambiguous words or phrases. A comparative experiment on the TREC 2007 Genomics Track data has been done.

Keywords

entropy; genomics; indexing; medical computing; query processing; software tools; MaxMatcher extraction tool; TREC 2007 genomic track data; concept-based genomic information retrieval; indexing; maximum entropy model; query expansion techniques; universal medical language system; Bioinformatics; Cancer; Computer science; Data mining; Entropy; Genomics; Hypertension; Information retrieval; Intrusion detection; Unified modeling language;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering and Computer Science (ICBECS), 2010 International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-5315-3

Type

conf

DOI

10.1109/ICBECS.2010.5462454

Filename

5462454