Unsupervised extraction of text segments from heterogeneous document collections

Authors:
Hong Cui
Affiliations:
University of Arizona, Tucson, AZ
Venue:
Proceedings of the 73rd ASIS&T Annual Meeting on Navigating Streams in an Information Ecosystem - Volume 47
Year:
2010

Citing 3
Cited 1

Statistical Models for Text Segmentation

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Semantic annotation of biosystematics literature without training examples

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From text to RDF triple store: an application for biodiversity literature

Proceedings of the 73rd ASIS&T Annual Meeting on Navigating Streams in an Information Ecosystem - Volume 47

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Abstract

This paper describes a simple, unsupervised bootstrapping procedure that identifies morphological description segments from heterogeneous biodiversity document collections. While the procedure is used to preprocess biodiversity literature for semantic annotation of morphological descriptions in our project, it also can be used to crawl the Web for morphological descriptions for a biodiversity niche search engine.