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Support vector machines (SVMs) are invaluable tools for many practical applications in artificial intelligence, e.g., classification and event recognition. However, popular SVM solvers are not sufficiently efficient for applications with a great deal of samples as well as a large number of features. In this paper, thus, we present NESVM, a fast gradient SVM solver that can optimize various SVM models,...
Sequential pattern mining is an important research task in many domains, such as biological science. In this paper, we study the problem of mining frequent patterns from sequences with wildcards. The user can specify the gap constraints with flexibility. Given a subject sequence, a minimal support threshold and a gap constraint, we aim to find frequent patterns whose supports in the sequence are no...
Recently, pattern matching with flexible gap constraints has attracted extensive attention especially in biological sequence analysis and mining patterns from sequences. An issue is to search Maximal Pattern Matching with Gaps and the One-Off Condition (MPMGOOC). Firstly, we introduce the concept of MPMGOOC. In order to solve the problem, we propose some special concepts of Nettree which is different...
In this paper, a new nonlinear structure called Nettree is proposed. A Nettree is different from a tree in that a node may have more than one parent. An algorithm, named Nettree for pattern Matching with flexible wildcard Constraints (NAMEIC), based on Nettree is designed to solve pattern matching with flexible wildcard constraints. The problem is exponential with regard to the pattern length m. We...
Pattern matching is fundamental in applications such as biological sequence analysis and text indexing. A wildcard gap matches any subsequence with a length between two user specified integers, therefore introducing much adaptability to patterns. However, most existing works require that gaps in a pattern be the same. In this paper, we define a new pattern matching problem where gaps are independently...
In this paper, we define a new research problem for mining approximate repeating patterns (ARP) with gap constraints, where the appearance of a pattern is subject to an approximate matching, which is very common in biological sciences. To solve the problem, we propose an ArpGap (Approximate repeating pattern mining with Gap constraints) algorithm with three major components for approximate repeating...
Pattern matching with wildcards is a complex problem and this problem has wide potential application in text search, biological sequences and information security etc. We propose a new algorithm called Quicksearch, for pattern matching with wildcards and length constraints based on key character location and subspace partition. This new algorithm increases by 40%-60% searching efficiency in comparison...
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