WEB MINING.Full Seminar Report
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25-01-2010, 06:26 PM


i'm here by sending a request for the full seminar and presentation report and Powerpoint presentation on the topic WEB MINING.

waiting for ur prompt reply...
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26-01-2010, 09:56 AM

Hey, visit this thread for more details on web mining:
Use Search at http://topicideas.net/search.php wisely To Get Information About Project Topic and Seminar ideas with report/source code along pdf and ppt presenaion
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29-10-2010, 05:26 PM

.doc   webmining.doc (Size: 68 KB / Downloads: 335)
Web Mining

Web Mining is the extraction of interesting and potentially useful patterns and implicit information from artifacts or activity related to the World¬Wide Web. There are roughly three knowledge discovery domains that pertain to web mining: Web Content Mining, Web Structure Mining, and Web Usage Mining. Web content mining is the process of extracting knowledge from the content of documents or their descriptions. Web document text mining, resource discovery based on concepts indexing or agent¬based technology may also fall in this category. Web structure mining is the process of inferring knowledge from the World¬Wide Web organization and links between references and referents in the Web. Finally, web usage mining, also known as Web Log Mining, is the process of extracting interesting patterns in web access logs.
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26-01-2011, 11:06 AM

i want to download above fileeeeeeeeeee
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27-01-2011, 10:57 AM

that is simple to download the attached file. just click on it.
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03-02-2012, 10:24 AM

to get information about the topic WEB MINING full report ,ppt and related topic refer the link bellow

topicideashow-to-web-mining-full-seminar and presentation-report










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plz send me infm on e-mining
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09-08-2012, 03:46 PM

Web mining

.doc   Web mining.doc (Size: 33 KB / Downloads: 18)

Web usage mining

Web usage mining is the process of extracting useful information from server logs i.e. users history. Web usage mining is the process of finding out what users are looking for on the Internet. Some users might be looking at only textual data, whereas some others might be interested in multimedia data.

Web structure mining

Web structure mining is the process of using graph theory to analyze the node and connection structure of a web site. According to the type of web structural data, web structure mining can be divided into two kinds:
1. Extracting patterns from hyperlinks in the web: a hyperlink is a structural component that connects the web page to a different location.
2. Mining the document structure: analysis of the tree-like structure of page structures to describe HTML or XML tag usage.
Web content mining
Mining, extraction and integration of useful data, information and knowledge from Web page contents. The heterogeneity and the lack of structure that permeates much of the ever expanding information sources on the World Wide Web, such as hypertext documents, makes automated discovery, organization, andsearch and indexing tools of the Internet and the World Wide Web such as Lycos, Alta Vista, WebCrawler, ALIWEB [6], MetaCrawler, and others provide some comfort to users, but they do not generally provide structural information nor categorize, filter, or interpret documents. In recent years these factors have prompted researchers to develop more intelligent tools for information retrieval, such as intelligent web agents, as well as to extend database and data mining techniques to provide a higher level of organization for semi-structured data available on the web. The agent-based approach to web mining involves the development of sophisticated AI systems that can act autonomously or semi-autonomously on behalf of a particular user, to discover and organize web-based information. The web content mining is differentiated from two different points of view [7]: Information Retrieval View and Database View. R. Kosala et al. [8] summarized the research works done for unstructured data and semi-structured data from information retrieval view. It shows that most of the researches use bag of words, which is based on the statistics about single words in isolation, to represent unstructured text and take single word found in the training corpus as features.

Web Usage mining Pros and Cons


Web usage mining essentially has many advantages which makes this technology attractive to corporations including the government agencies. This technology has enabled e-commerce to do personalized marketing, which eventually results in higher trade volumes. The government agencies are using this technology to classify threats and fight against terrorism. The predicting capability of the mining application can benefits the society by identifying criminal activities. The companies can establish better customer relationship by giving them exactly what they need. Companies can understand the needs of the customer better and they can react to customer needs faster. The companies can find, attract and retain customers; they can save on production costs by utilizing the acquired insight of customer requirements. They can increase profitability by target pricing based on the profiles created. They can even find the customer who might default to a competitor the company will try to retain the customer by providing promotional offers to the specific customer, thus reducing the risk of losing a customer or customers.


Web usage mining by itself does not create issues, but this technology when used on data of personal nature might cause concerns. The most criticized ethical issue involving web usage mining is the invasion of privacy. Privacy is considered lost when information concerning an individual is obtained, used, or disseminated, especially if this occurs without their knowledge or consent.[1] The obtained data will be analyzed, and clustered to form profiles; the data will be made anonymous before clustering so that there are no personal profiles.[1] Thus these applications de-individualize the users by judging them by their mouse clicks. De-individualization, can be defined as a tendency of judging and treating people on the basis of group characteristics instead of on their own individual characteristics and merits.[1]

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