We have reviewed the papers through a series of three levels of review, which comprises of Senior Academicians, Industry professionals and Professors from premier Institutions and Universities.
Usage data captures the identity or origin of Web users along with their browsing behavior at a Web site. Web usage mining itself can be classified further depending on the kind of usage data considered: The user logs are collected by the Web server.
Typical data includes IP address, page reference and access time. Commercial application servers have significant features to enable e-commerce applications to be built on top of them with little effort. A key feature is the ability to track various kinds of business events and log them in application server logs.
New kinds of events can be defined in an application, and logging can be turned on for them thus generating histories of these specially defined events. It must be noted, however, that many end applications require a combination of one or more of the techniques applied in the categories above.
Studies related to work  are concerned with two areas: Costa and Seco demonstrated that web log mining can be used to extract semantic information hyponymy relationships in particular about the user and a given community.
Pros[ edit ] Web usage mining essentially has many advantages which makes this technology attractive to corporations including government agencies. This technology has enabled e-commerce to do personalized marketingwhich eventually results in higher trade volumes.
Government agencies are using this technology to classify threats and fight against terrorism.
The predicting capability of mining applications can benefit society by identifying criminal activities. Companies can establish better customer relationship by understanding the needs of the customer better and reacting to customer needs faster.
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 customers 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.
More benefits of web usage mining, particularly in the area of personalizationare outlined in specific frameworks such as the Probabilistic Latent Semantic Analysis model, which offer additional features to the user behavior and access pattern.
These models also demonstrate a capability in web usage mining technology to address problems associated with traditional techniques such as biases and questions regarding validity since the data and patterns obtained are not subjective and do not degrade over time.
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. 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.
The growing trend of selling personal data as a commodity encourages website owners to trade personal data obtained from their site. The companies which buy the data are obliged make it anonymous and these companies are considered authors of any specific release of mining patterns.
They are legally responsible for the contents of the release; any inaccuracies in the release will result in serious lawsuits, but there is no law preventing them from trading the data. Some mining algorithms might use controversial attributes like sex, race, religion, or sexual orientation to categorize individuals.
These practices might be against the anti-discrimination legislation. This process could result in denial of service or a privilege to an individual based on his race, religion or sexual orientation.
Right now this situation can be avoided by the high ethical standards maintained by the data mining company. The collected data is being made anonymous so that, the obtained data and the obtained patterns cannot be traced back to an individual.
Web structure mining[ edit ] You can help by adding to it.Data mining in e-commerce is all about integrating statistics, databases and artificial intelligence together with some subjects to form a new idea or a new integrated technology for .
Data mining in e-commerce: A survey April · Sadhana Data mining has matured as a field of basic and applied research in computer science in general and e-commerce in particular. APPLICATIONS OF DATA MINING TO ELECTRONIC COMMERCE 7 perspective,sincecustomersareinteractingwiththecomputerdirectly,productassortments, virtual product displays, and other merchandising interfaces can be modiﬁed dynamically, and even can be personalized to individual customers.
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3. DATA MINING AND CONSUMER BEHAVIOR IN E-COMMERCE In the past few years, the development of the World Wide Web exceeded all expectations. Retrieving data has become a very difficult task taking into consideration the impressive variety of the Web.
Web consists of several types of data such as text data, images, audio or video, structured records such as lists or tables and hyperlinks. The leading source for e-commerce news, strategies and research.
Including webinars, blogs and e-retailer rankings, Top