A Review Of Trends In Research On Web Mining

In recent years the growth of the World Wide Web exceeded all expectations. Today there are several billions of HTML documents, pictures and other multimedia files available via internet and the number is still rising. But considering the impressive variety of the web, retrieving interesting content has become a very difficult task.So, the World Wide Web is a fertile area for data mining research.Web mining is a research topic which combines two of the activated research areas: Data Mining and World Wide Web. Web mining research relates to several research communities such as Database, information Retrieval and Artificial intelligence, visualization.This paper reviews the research and application issues in web mining besides proving an overall view of Web mining

A Survey on Web Usage Mining, Applications and Tools

World Wide Web is a vast collection of unstructured web documents like text, images, audio, video or Multimedia content.  As web is growing rapidly with millions of documents, mining the data from the web is a difficult task. To mine various patterns from the web is known as Web mining. Web mining is further classified as content mining, structure mining and web usage mining. Web usage mining is the data mining technique to mine the knowledge of usage of web data from World Wide Web. Web usage mining extracts useful information from various web logs i.e. users usage history. This is useful for better understanding and serve the people for better web applications. Web usage mining not only useful for the people who access the documents from the World Wide Web, but also it useful for many applications like e-commerce to do personalized marketing, e-services, the government agencies to classify threats and fight against terrorism, fraud detection, to identify criminal activities, the companies can establish better customer relationship and can improve their businesses by analyzing the people buying strategies etc. This paper is going to explain in detail about web usage mining and how it is helpful. Web Usage Mining has seen rapid increase towards research and people communities

Web Usage Mining for UUM Learning Care Using Association Rules

The enormous of information on the World Wide Web makes it obvious candidate for data mining research. Application of data mining techniques to the World Wide Web referred as Web mining where this term has been used in three distint ways; Web Content Mining, Web Structure Mining and Web Usage Mining. E-Learning is one of the Web based application where it will facing with large amount of data. In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. Web usage mining consists of three main phases, namely Data Preprocessing. Pattern Discovering and Patern Analysis. Main resources, server log files become a set of raw data where it's must go through with all the Web usage mining technique, Web usage mining approach has been combined with the basic Association Rules, Apriori Algorithm to optimize the content of the university E-Learning portal. Finally this paper will present an overview of results with the analysis and Web administrator can use the findings for the suitable valuable actions

A Survey to Fix the Threshold and Implementation for Detecting Duplicate Web Documents

The drastic development in the information accessible on the World Wide Web has made the employment of automated tools to locate the information resources of interest, and for tracking and analyzing the same a certainty. Web Mining is the branch of data mining that deals with the analysis of World Wide Web. The concepts from various areas such as Data Mining, Internet technology and World Wide Web, and recently, Semantic Web can be said as the origin of web mining. Web mining can be defined as the procedure of determining hidden yet potentially beneficial knowledge from the data accessible in the web. Web mining comprise the sub areas: web content mining, web structure mining, and web usage mining. Web content mining is the process of mining knowledge from the web pages besides other web objects. The process of mining knowledge about the link structure linking web pages and some other web objects is defined as Web structure mining. Web usage mining is defined as the process of mining the usage patterns created by the users accessing the web pages. The search engine technology has led to the development of World Wide. The search engines are the chief gateways for access of information in the web. The ability to locate contents of particular interest amidst a huge heap has turned businesses beneficial and productive. The search engines respond to the queries by employing the process of web crawling that populates an indexed repository of web pages. The programs construct a confined repository of the segment of the web that they visit by navigating the web graph and retrieving pages. There are two main types of crawling, namely, Generic and Focused crawling. Generic crawlers crawls documents and links of diverse topics. Focused crawlers limit the number of pages with the aid of some prior obtained specialized knowledge. The systems that index, mine, and otherwise analyze pages (such as, the search engines) are provided with inputs from the repositories of web pages built by the web crawlers. The drastic development of the Internet and the growing necessity to incorporate heterogeneous data is accompanied by the issue of the existence of near duplicate data. Even if the near duplicate data don’t exhibit bit wise identical nature they are remarkably similar. The duplicate and near duplicate web pages either increase the index storage space or slow down or increase the serving costs which annoy the users, thus causing huge problems for the web search engines. Hence it is inevitable to design algorithms to detect such pages

Analysis of Web Log from Database System utilizing E-web Miner Algorithm

Enormous content of information on the World Wide Web makes it clear for contender for data mining research. Data Mining Technique application is used to the World Wide Web referred as Web mining where this term has been used diverse ways. Web Log Mining is one of the Web based application where it confronts with large amount of log information. In order to produce the web log through portal usage patterns and user behaviors’ recognition, this intended work is an endeavor to apply an efficient web mining algorithm for web log analysis, which is applied to identify the context related with the web design of an e- business web portal that requests security. Because of tremendous utilization of web, web log documents have a tendency to become large resulting in noisy data files. It can find the browsing patterns of client and some class of relationships between the web pages. Here we analyze the logs using web mining algorithm. Whatever the result we will get compare within the Apriori, AprioriAll and E-Web Miner Algorithm. Through the analysis we recognize that web mining algorithm called E-web miner i.e. Efficient Web Mining performs better considering space and time complexity. It can likewise be verified by comparison, candidate sets are much smaller and our results show number of database scanning get reduced due to implementation of E-Web Miner Algorithm. DOI: 10.17762/ijritcc2321-8169.15077