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DIS
2010
Springer

Sparse Substring Pattern Set Discovery Using Linear Programming Boosting

11 years 10 months ago
Sparse Substring Pattern Set Discovery Using Linear Programming Boosting
In this paper, we consider finding a small set of substring patterns which classifies the given documents well. We formulate the problem as 1 norm soft margin optimization problem where each dimension corresponds to a substring pattern. Then we solve this problem by using LPBoost and an optimal substring discovery algorithm. Since the problem is a linear program, the resulting solution is likely to be sparse, which is useful for feature selection. We evaluate the proposed method for real data such as movie reviews.
Kazuaki Kashihara, Kohei Hatano, Hideo Bannai, Mas
Added 10 Feb 2011
Updated 10 Feb 2011
Type Journal
Year 2010
Where DIS
Authors Kazuaki Kashihara, Kohei Hatano, Hideo Bannai, Masayuki Takeda
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