Artificial Immune System based Firefly Approach for Web Page Classification

WWW is now a famous medium by which people all around the world can spread and gather the information of all kinds. But web pages of various sites that are generated dynamically contain undesired information also. This information is called noisy or irrelevant content. Web publishing techniques create numerous information sources published as HTML pages. Navigation panels, Table of content, advertisements, copyright statements, service catalogs, privacy policies etc. on web pages are considered as relevant and irrelevant content. This paper discusses various methods for web pages classification and a new approach for content extraction based on firefly feature extraction method with danger theory for web pages classification

A Proposed Technique for Finding Pattern from Web Usage Data

There are various ways of web page classification but they take higher time to compute with lesser accuracy. Hence, there is a need to invent an efficient algorithm in order to reduce time and increase web page classification result. Artificial Immune System (AIS) which has the characteristic of high self-adaptation and self-construction inspired from the function of biological immune system. An ensemble approach of AIS and tree based classifier has used the hybrid approach. This inspired the scholars to use such hybrid approach for Structure based web page classification

An Overview of the Use of Neural Networks for Data Mining Tasks

In the recent years the area of data mining has experienced a considerable demand for technologies that extract knowledge from large and complex data sources. There is a substantial commercial interest as well as research investigations in the area that aim to develop new and improved approaches for extracting information, relationships, and patterns from datasets. Artificial Neural Networks (NN) are popular biologically inspired intelligent methodologies, whose classification, prediction and pattern recognition capabilities have been utilised successfully in many areas, including science, engineering, medicine, business, banking, telecommunication, and many other fields. This paper highlights from a data mining perspective the implementation of NN, using supervised and unsupervised learning, for pattern recognition, classification, prediction and cluster analysis, and focuses the discussion on their usage in bioinformatics and financial data analysis tasks

Annoyancetech Vigilante Torts and Policy

The twenty-first century has ushered in demand by some Americans for annoyancetech devices—novel electronic gadgets that secretly fend off, punish, or comment upon perceived antisocial and annoying behaviors of others. Manufacturers, marketers, and users of certain annoyancetech devices, however, face potential tort liability for personal and property damages suffered by the targets of this “revenge by gadget.” Federal, state, and local policymakers should start the process of coming to pragmatic terms with the troubling rise in the popularity of annoyancetech devices. This is an area of social policy that cries out for thoughtful and creative legislative solutions