Web Data Mining through Software Agents

Abstract

Web data mining research efforts lead to user or group of user's satisfaction by providing accurate and relevant information retrieval; by learning about user's demands so that services can target specific groups or even individual users and by providing personalized service. Due to the explosive growth of web content in the internet world in the past few years, there is tremendous requirement and scope of doing research in the category of e-commerce agents. Also user requirements such as getting accurate information in a prompt manner are not getting fulfilled as per their expectations. This has motivated the researcher to pursue his research in the field of web data mining through software agents. This paper has highlighted the implementations of software agents for e-commerce applications.

Improved Memetic Algorithm Enabled Intelligent Multi Agent (IMAEIMA) System for Web Mining

“…From this the term frequency is calculated using function (2). The quality of population is calculated using function (3). For local search process the hueristic function (1) is used, and select the population for further process.…”

“…The web information is grouped into clusters relevant to the query; satisfying user needs and yields better usage of web surfing time [2]. Shakti Kundu et al, (2017) introduced a new system called WEBMINTEL, is a multi agent system with three offers: reject, accept or add to cart, and these offers are intelligently executed based on prior knowledge [3]. Melita et al (2012) reviewed the characteristics of Genetic Algorithms, GA based search techniques, problems in implementation and available methods suitable for web search optimization.…”