Abstract
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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Kiyavitskaya, N., Zeni, N., Mich, L., Cordy, J.R., Mylopoulos, J. (2006). Text Mining Through Semi Automatic Semantic Annotation. In: Reimer, U., Karagiannis, D. (eds) Practical Aspects of Knowledge Management. PAKM 2006. Lecture Notes in Computer Science(), vol 4333. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11944935_13
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DOI: https://doi.org/10.1007/11944935_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49998-5
Online ISBN: 978-3-540-49999-2
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