Conference proceeding
A Mixture Language Model for Class-Attribute Mining from Biomedical Literature Digital Library
2008 IEEE International Conference on Bioinformatics and Biomedicine, Proceedings, pp 17-22
01 Jan 2008
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
We define and study a novel text mining problem for biomedical literature digital library, referred to as the class-attribute mining. Given a collection of biomedical literature from a digital library addressing a set of objects (e.g., proteins) and their descriptions (e.g., protein functions), the tasks of class-attribute mining include: (1) to identify and summarize latent classes in the space of objects, (2) to discover latent attribute themes in the space of object descriptions, and (3) to summarize the commonalities and differences among identified classes along each attribute theme. We approach this mining problem through a mixture language model and estimate the parameters of the model using the EM algorithm. We demonstrate the effectiveness of the model with an application called protein community identification and annotation from Medline, the largest biomedical literature digital library with more than 16 millions abstracts.
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Details
- Title
- A Mixture Language Model for Class-Attribute Mining from Biomedical Literature Digital Library
- Creators
- Xiaohua Zhou - Drexel UniversityXiahoua Hu - Drexel UniversityXiaohua Zhang - Drexel UniversityDaniel D. Wu - Drexel UniversityTingting He - Central China Normal UniversityAijing Luo - Cent South Univ, Changsha, Hunan, Peoples R China
- Publication Details
- 2008 IEEE International Conference on Bioinformatics and Biomedicine, Proceedings, pp 17-22
- Conference
- 2008 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (Philadelphia, Pennsylvania, United States, 03 Nov 2008–05 Nov 2008)
- Series
- IEEE International Conference on Bioinformatics and Biomedicine-BIBM
- Publisher
- IEEE
- Number of pages
- 3
- Grant note
- 239667 / PA Dept of Health IIS 0448023 / NSF Career Grant; National Science Foundation (NSF); NSF - Office of the Director (OD) 240205; 240196 / PA Dept of Health Tobacco Settlement Formula Grant CCF 0514679 / NSF; National Science Foundation (NSF) B07042 / Programme of Introducing Talents of Discipline to Universities; Ministry of Education, China - 111 Project
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000264284200003
- Scopus ID
- 2-s2.0-58049173374
- Other Identifier
- 991019170512704721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Mathematical & Computational Biology