Abstract
Identifying temporal information of topics from a document set typically involves constructing a time decomposition of the time period associated with the document set. In an earlier work, we formulated several metrics on a time decomposition, such as size, information loss, and variability, and gave dynamic programming based algorithms to construct time decompositions that are optimal with respect to these metrics. Computing information loss values for all subintervals of the time period is central to the computation of optimal time decompositions. This paper proposes several algorithms to assist in more efficiently constructing an optimal time decomposition. More efficient, parallelizable algorithms for computing loss values are described. An efficient top-down greedy heuristic to construct an optimal time decomposition is also presented. Experiments to study the performance of this greedy heuristic were conducted. Although lossy time decompositions constructed by the greedy heuristic are suboptimal, they seem to be better than the widely used uniform length decompositions.
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Chundi, P., Zhang, R., Rosenkrantz, D.J. (2005). Efficient Algorithms for Constructing Time Decompositions of Time Stamped Documents. In: Andersen, K.V., Debenham, J., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2005. Lecture Notes in Computer Science, vol 3588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11546924_50
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DOI: https://doi.org/10.1007/11546924_50
Publisher Name: Springer, Berlin, Heidelberg
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