分类： 系统运维
2010-04-14 16:51:20
Web mining - is the application of techniques to discover patterns from the . According to analysis targets, web mining can be divided into three different types, which are Web usage mining, Web content mining and Web structure mining.
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Web usage mining is the process of finding out what users are looking for on the . Some users might be looking at only textual data, whereas some others might be interested in multimedia data. Web usage mining also helps find patterns for a particular group of people, or for Internet users in a particular region.
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 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 or tag usage.
Web mining essentially has many advantages which makes this technology attractive to corporations including the government agencies. This technology has enabled ecommerce 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 mining the technology itself doesn’t create issues, but this
technology when used on data of personal nature might cause concerns.
The most criticized ethical issue involving web 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 .
The obtained data will be analyzed, and clustered to form profiles; the
data will be made anonymous before clustering so that no individual can
be linked directly to a profile. But usually the group profiles are
used as if they are personal profiles .
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.
Another important concern is that the companies collecting the data for a
specific purpose might use the data for a totally different purpose,
and this essentially violates the user’s interests. The growing trend of
selling personal data as a commodity encourages website owners to trade
personal data obtained from their site. This trend has increased the
amount of data being captured and traded increasing the likeliness of
one’s privacy being invaded. 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.
The applications make it hard to identify the use of such controversial
attributes, and there is no strong rule against the usage of such
algorithms with such attributes. 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. It might look as if
this poses no threat to one’s privacy, actually many extra information
can be inferred by the application by combining two separate
unscrupulous data from the user
