Informatics Publishing Limited

Karimella Vikram ¹, K. Venkatesh Reddy ¹, A. Goverdhan ², Niraj Upadyaya ³

Affiliations
1 Narayanadri Institute of Technology & Science, Rajampet, Kadapa (D), IN
2 JNTUH, RangaReddy (D), IN
3 J.B.I.E.T, Hyderabad, IN

Abstract

System for recognition of online handwritten characters has been presented for Indian writing systems. A handwritten character is represented as a sequence of strokes whose features are extracted and classi_ed. Support vector machines have been used for constructing the stroke recognition engine. The results have been presented after testing the system on Devanagari and Telugu scripts. A system for online recognition of handwritten Tamil characters is presented. A handwritten character is constructed by executing a sequence of strokes. A structure- or shape-based representation of a stroke is used in which a stroke is represented as a string of shape features. Using this string representation, an unknown stroke is identified by comparing it with a database of strokes using a flexible string matching procedure. A full character is recognized by identifying all the component strokes. Character termination, is determined using a finite state automaton. Development of similar systems for other Indian scripts is outlined.

Keywords

Shape Features, Stroke Identification, FSA.

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C. Ramesh ¹, K. V. Chalapati Rao ¹, A. Goverdhan ²

Affiliations
1 Department of Computer Science and Engineering, CVR College of Engineering, Ibrahimpatnam, R.R.District, Andhra Pradesh, IN
2 JNTUH College of Engineering, Jagityala, Karimnagar District, Andhra Pradesh, IN

Abstract

With the rapid growth of internet technologies, Web has become a huge repository of information and keeps growing exponentially under no editorial control. However the human capability to read, access and understand Web content remains constant. This motivated researchers to provide Web personalized online services such as Web recommendations to alleviate the information overload problem and provide tailored Web experiences to the Web users. Recent studies show that Web usage mining has emerged as a popular approach in providing Web personalization. However conventional Web usage based recommender systems are limited in their ability to use the domain knowledge of the Web application. The focus is only on Web usage data. As a consequence the quality of the discovered patterns is low. In this paper, we propose a novel framework integrating semantic information in the Web usage mining process. Sequential Pattern Mining technique is applied over the semantic space to discover the frequent sequential patterns. The frequent navigational patterns are extracted in the form of Ontology instances instead of Web page views and the resultant semantic patterns are used for generating Web page recommendations to the user. Experimental results shown are promising and proved that incorporating semantic information into Web usage mining process can provide us with more interesting patterns which consequently make the recommendation system more functional, smarter and comprehensive.

Keywords

Web Usage Mining, Semantic Web, Domain Ontology, Sequential Pattern Mining, Recommender Systems.

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