Abstract
Conventional automatic text annotation tools mostly extract named entities from texts and annotate them with information about persons, locations, and dates, etc. Such kind of entity type information, however, is insufficient for machines to understand the context or facts contained in the texts. This paper presents a general text categorization approach to categorize text segments into broader subject categories, such as categorizing a text string into a category of paper title in Mathematics or a category of conference name in Computer Science. Experimental results confirm its wide applicability to various digital library applications.
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Chiao, HC., Pu, HT., Chien, LF. (2005). Annotating Text Segments Using a Web-Based Categorization Approach. In: Fox, E.A., Neuhold, E.J., Premsmit, P., Wuwongse, V. (eds) Digital Libraries: Implementing Strategies and Sharing Experiences. ICADL 2005. Lecture Notes in Computer Science, vol 3815. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11599517_37
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DOI: https://doi.org/10.1007/11599517_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30850-8
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