This paper proposes a novel tree kernel-based method with rich syntactic and semantic information for the extraction of semantic relations between named entities. With a parse tree and an entity pair, we first construct a rich semantic relation tree structure to integrate both syntactic and semantic information. And then we propose a context-sensitive convolution tree kernel, which enumerates b...

Visualisations of abstract data are believed to assist the searcher by providing an overview of the semantic structure of a document collection whereby semantically similar items tend to cluster in space. Cribbin and Chen (2001) found that similarity data represented using minimum spanning tree (MST) graphs provided greater levels of support to users when conducting a range of information seeki...

In the past decades, kernel methods are enthusiastically explored for relation extraction. This paper proposes a penalty tree similarity algorithm by extending the dependency tree kernel. Dependency tree kernel computes the similarity of two parse trees by enumerating their matched sub-trees. The penalty tree similarity, however, not only consider the similar structures of the parse trees, but ...

A new inductive data mining method for automatic generation of decision trees from data (GPTree) is presented. Compared with other decision tree induction techniques that are based upon recursive partitioning employing greedy searches to choose the best splitting attribute and value at each node therefore will necessarily miss regions of the search space, GPTree can overcome the problem. In add...

The classification-tree method developed by Grochtmann et al. provided a useful approach for constructing test cases from functional specifications. It was automated by Chen and Poou through their tree construction methodology. In a follow-up study, Chen and Poon found that the cffectiveness of constructing lcgitimate test cases could be improved under certain circumstances via a classification...

This paper proposes a tree kernel with contextsensitive structured parse tree information for relation extraction. It resolves two critical problems in previous tree kernels for relation extraction in two ways. First, it automatically determines a dynamic context-sensitive tree span for relation extraction by extending the widely-used Shortest Path-enclosed Tree (SPT) to include necessary conte...

Reconstruction of an evolutionary history for a set of organisms is an important research subject in computational biology. One approach motivated by graph theory constructs a relationship graph based on pairwise evolutionary closeness. The approach builds a tree representation equivalent to this graph such that leaves of the tree, corresponding to the organisms, are within a specified distance...

The main aim of this paper is to develop a suitable regression analysis model for describing the relationship between the index efficiency and the parameters of the Rival Penalized Competitive Learning Binary Tree (RPCLb-tree). RPCL-b-tree is a hierarchical indexing structure built with a hierarchical RPCL clustering implementation, which transforms the feature space into a sequence of nested c...