Knowledge representation for commonsense reasoning with text
Computational Linguistics
Natural language understanding (2nd ed.)
Natural language understanding (2nd ed.)
Serial computations of Levenshtein distances
Pattern matching algorithms
Survey of the state of the art in human language technology
Survey of the state of the art in human language technology
A knowledge-driven approach to text meaning processing
HLT-NAACL-TEXTMEANING '03 Proceedings of the HLT-NAACL 2003 workshop on Text meaning - Volume 9
Automatic sense disambiguation of the near-synonyms in a dictionary entry
CICLing'03 Proceedings of the 4th international conference on Computational linguistics and intelligent text processing
Drive-by language identification: a byproduct of applied prototype semantics
CICLing'10 Proceedings of the 11th international conference on Computational Linguistics and Intelligent Text Processing
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In this paper we present a novel approach to map textual entities such as words, phrases, sentences, paragraphs or arbitrary text fragments onto artificial structures which we call "Text Sense Representation Trees" (TSR trees). These TSR trees represent an abstract notion of the meaning of the respective text, subjective to an abstract "common" understanding within the World Wide Web. TSR Trees can be used to support text and language processing systems such as text categorizers, classifiers, automatic summarizers and applications of the Semantic Web. We will explain how to construct the TSR tree structures and how to use them properly; furthermore we describe some preliminary evaluation results.