ICTACT Journal on Soft Computing

A. John ¹, M. Sugumaran ², R. S. Rajesh ¹

Affiliations
1 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, IN
2 Department of Computer Science and Engineering, Pondicherry Engineering College, IN

Abstract

Indexing and query processing is an emerging research field in spatio - temporal data. Most of the real-time applications such as location based services, fleet management, traffic prediction and radio frequency identification and sensor networks are based on spatio-temporal indexing and query processing. All the indexing and query processing applications is any one of the forms, such as spatio index access and supporting queries or spatio-temporal indexing method and support query or temporal dimension, while in spatial data it is considered as the second priority. In this paper, give the survey of the various uncertain indexing and query processing techniques. Most of the existing survey works on spatio-temporal are based on indexing methods and query processing, but presented separately. Both the indexing and querying are related, hence state - of - art of both the indexing and query processing techniques are considered together. This paper gives the details of spatio-temporal data classification, various types of indexing methods, query processing, application areas and research direction of spatio-temporal indexing and query processing.

Keywords

Uncertain Data, Spatio-Temporal Index, Spatio-Temporal Queries, Skyline Query, Top-K Query, Nearest-Neighbor Query.

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S. Arun Mozhi Selvi ¹, R. S. Rajesh ²

Affiliations
1 Department of Information Technology, Dr. Sivanthi Aditanar College of Engineering, IN
2 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, IN

Abstract

Spam is commonly defined as unsolicited email messages and the goal of spam categorization is to distinguish between spam and legitimate email messages. The economics of spam details that the spammer has to target several recipients with identical and similar email messages. As a result a dynamic knowledge sharing effective defense against a substantial fraction of spam has to be designed which can alternate the burdens of frequent training stand alone spam filter. A weighted email attribute based classification is proposed to mainly focus to encounter the issues in normal email system. These type of classification helps to formulate an effective utilization of our email system by combining the concepts of Bayesian Spam Filtering Algorithm, Iterative Dichotmiser 3(ID3) Algorithm and Bloom Filter. The details captured by the system are processed to track the original sender causing disturbances and prefer them to block further mails from them. We have tested the effectiveness of our scheme by collecting offline data from Yahoo mail&Gmail dumps. This proposal is implemented using .net and sample user-Id for knowledge base.

Keywords

Spam, Bayesian, IMAP, ID3.

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