Abstract
The goal of this paper is to provide a visual structure to view the temporal and thematic content of English news documents. This paper combines both information extraction techniques and visualization techniques to visualize the documents content. Topical information present in the documents are extracted by applying Booksteins model and by calculating the various measures associated with the model. Temporal information is extracted as date information from the documents. Later the extracted information is converted into a signal and both discrete and continuous wavelet transfor-mations are applied over the signal. The content of the document is visualized at varying levels of detail by multi resolution analysis techniques available in wavelets. This gives a wavelet based visualization model which enables us to view the spread of topics across a document, the portions of the document that are most involved in topic description, and the contribution of documents in the corpus from the temporal perspective.
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Mala, T., Geetha, T.V., Kumar, S. (2006). Topical and Temporal Visualization Using Wavelets. In: Yang, Q., Webb, G. (eds) PRICAI 2006: Trends in Artificial Intelligence. PRICAI 2006. Lecture Notes in Computer Science(), vol 4099. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36668-3_91
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DOI: https://doi.org/10.1007/978-3-540-36668-3_91
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