scholarly journals A Time-Sequence Similarity Matching Algorithm for Seismological Relevant Zones

2006 ◽  
Vol 17 (1) ◽  
pp. 185 ◽  
Author(s):  
Shao-Chun WU
Keyword(s):  
Sequence Similarity ◽  
Time Sequence ◽  
Similarity Matching ◽  
Matching Algorithm

A LEXICAL DECISION TREE SCHEME FOR SUPPORTING SCHEMA MATCHING

2011 ◽  
Vol 10 (03) ◽  
pp. 519-537 ◽  
Author(s):  
BEEN-CHIAN CHIEN ◽  
SHIANG-YI HE
Keyword(s):  
Decision Tree ◽  
Lexical Decision ◽  
Structural Similarity ◽  
Schema Matching ◽  
Similarity Matching ◽  
Matching Method ◽  
Matching Algorithm ◽  
Essential Step ◽  
Structure Similarity ◽  
Two Phases

To manipulate semantic web and integrate different data sources efficiently, automatic schema matching plays a key role. A generic schema matching method generally includes two phases: the linguistic similarity matching phase and the structural similarity matching phase. Since linguistic matching is an essential step for effective schema matching, developing a high accurate linguistic similarity matching scheme is required. In this paper, a schema matching approach called Similarity Yield Matcher (SYM) is proposed. In SYM, a lexical decision tree is presented to determine the linguistic similarity matching of the first phase. A structural matching algorithm is then proposed to find the structure similarity between two tree schemas. The proposed schema matching approach was evaluated by testing on several benchmarks of real schemas and comparing with other methods. The experimental results show that the proposed lexical decision tree substantially improves the linguistic similarity matching effectively and efficiently. The proposed SYM algorithm also performs high effectiveness on 1–1 schema matching.

Construction and Match of Question Templates Based on Domain Ontology and Semantic Block

2013 ◽  
Vol 373-375 ◽  
pp. 1776-1779 ◽  
Author(s):  
Xin Hua Zhu ◽  
Cheng Gong ◽  
Hong Chao Chen
Keyword(s):  
Success Rate ◽  
Template Matching ◽  
Semantic Analysis ◽  
Sequence Similarity ◽  
Domain Ontology ◽  
Processing Method ◽  
Semantic Features ◽  
Template Match ◽  
Matching Algorithm ◽  
Template Library

Compared with other methods, the question sentences processing method based on sentence-template match avoids complex lexical, syntactic and semantic analysis, but the size of the question template library is the key. To solve this problem, this paper used domain ontology and semantic block to build question templates, and added synonymous question templates into question model, then proposed a question template matching algorithm based on the semantic similarity, length similarity and sequence similarity. The experimental results show that this method greatly improves the success rate to extract the semantic features of users question sentences.

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