Text Mining Through Semi Automatic Semantic Annotation
Author(s) -
Nadzeya Kiyavitskaya,
Nicola Zeni,
Luisa Mich,
James R. Cordy,
John Mylopoulos
Publication year - 2006
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
ISBN - 3-540-49998-9
DOI - 10.1007/11944935_13
Subject(s) - annotation , computer science , semantic annotation , information retrieval , natural language processing , artificial intelligence
The Web is the greatest information source in human history. Unfortunately, mining knowledge out of this source is a laborious and error-prone task. Many researchers believe that a solution to the problem can be founded on semantic annotations that need to be inserted in web-based documents and guide information extraction and knowledge mining. In this paper, we further elaborate a tool-supported process for semantic annotation of documents based on techniques and technologies traditionally used in software analysis and reverse engineering for large-scale legacy code bases. The outcomes of the paper include an experimental evaluation framework and empirical results based on two case studies adopted from the Tourism sector. The conclusions suggest that our approach can facilitate the semi-automatic annotation of large document bases.
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