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Unformatted text preview: lustering of client information or data
items on Web transaction logs, can facilitate the development and execution of future marketing strategies, both online and o -line, such as automated return mail to clients falling within a certain cluster,
or dynamically changing a particular site for a client,
on a return visit, based on past classi cation of that
client. 4 Analysis of Discovered Patterns The discovery of Web usage patterns, carried out by
techniques described earlier, would not be very useful
unless there were mechanisms and tools to help an analyst better understand them. Hence, in addition to
developing techniques for mining usage patterns from
Web logs, there is a need to develop techniques and
tools for enabling the analysis of discovered patterns.
These techniques are expected to draw from a number of elds including statistics, graphics and visualization, usability analysis, and database querying. In
this section we provide a survey of the existing tools and techniques. Usage analysis of Web access behavior being a very new area, there is very little work in it,
and correspondingly this survey is not very extensive.
Visualization has been used very successfully in
helping people understand various kinds of phenomena, both real and abstract. Hence it is a natural
choice for understanding the behavior of Web users.
Pitkow, et al 45] have developed the WebViz system
for visualizing WWW access patterns. A Web path
paradigm is proposed in which sets of server log entries are used to extract subsequences of Web traversal patterns called Web paths. WebViz allows the analyst to selectively analyze the portion of the Web that
is of interest by ltering out the irrelevant portions.
The Web is visualized as a directed graph with cycles, where nodes are pages and edges are (inter-page)
On-Line Analytical Processing (OLAP) is emerging as a powerful paradigm for strategic analysis of
databases in business settings. It has been recently
demonstrated that the functional and performance
needs of OLAP require that new information structures be designed. This has led to the development
of the data cube information model 18], and techniques for its e cient implementation 2, 22, 50]. Recent work 15] has shown that the analysis needs of
Web usage data have much in common with those of a
data warehouse, and hence OLAP techniques are quite
applicable. The access information in server logs is
modeled as an append-only history, which grows over
time. Since the size of server logs grows quite rapidly,
it may not be possible to provide on-line analysis of
all of it. Therefore, there is a need to summarize the
log data, perhaps in various ways, to make its on-line
analysis feasible. Making portions of the log selectively (in)visible to various analysts may be required
for security reasons.
One of the reasons attributed to the great success of
relational database technology has been the existence
of a high-level, declarative, query language, which allows an application to express what conditions must
be satis ed by the data it needs, rather than having to
specify how to get the required data. Give...
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- Spring '14