ICTACT Journal on Soft Computing

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Supervised Alias Name Validation Using Statistical Similarity Coefficients


Affiliations
1 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, India
     

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Alias name is the surnames for a known name. Extracting and validating alias names is an interesting research topic in language processing and has a number of Natural language processing applications like Information extraction, Information retrieval, Sentimental analysis, Question and answering. Alias name validation involves the process of validating whether a name is alias name or not. In this work, seven statistical similarity coefficients were used as features in classifier to validate alias names. For each name-alias pair, seven statistical similarity coefficient values were calculated and used as features to train a classifier. The trained classifier is then employed to classify whether a name-alias pair is valid or not. Experiments were conducted using Indian name-alias data that has data for 15 persons containing 35 name-alias pairs. Results show that SVM classifier with Radial Basis Function Kernel outperforms all the other classifiers in terms of overall accuracy.

Keywords

Alias Name Extraction, Information Extraction, Web Mining.
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  • Supervised Alias Name Validation Using Statistical Similarity Coefficients

Abstract Views: 262  |  PDF Views: 2

Authors

A. Suruliandi
Department of Computer Science and Engineering, Manonmaniam Sundaranar University, India
P. Selvaperumal
Department of Computer Science and Engineering, Manonmaniam Sundaranar University, India
T. Dhiliphan Rajkumar
Department of Computer Science and Engineering, Manonmaniam Sundaranar University, India

Abstract


Alias name is the surnames for a known name. Extracting and validating alias names is an interesting research topic in language processing and has a number of Natural language processing applications like Information extraction, Information retrieval, Sentimental analysis, Question and answering. Alias name validation involves the process of validating whether a name is alias name or not. In this work, seven statistical similarity coefficients were used as features in classifier to validate alias names. For each name-alias pair, seven statistical similarity coefficient values were calculated and used as features to train a classifier. The trained classifier is then employed to classify whether a name-alias pair is valid or not. Experiments were conducted using Indian name-alias data that has data for 15 persons containing 35 name-alias pairs. Results show that SVM classifier with Radial Basis Function Kernel outperforms all the other classifiers in terms of overall accuracy.

Keywords


Alias Name Extraction, Information Extraction, Web Mining.

References