Database Reference
In-Depth Information
by joining a dimension table and a fact table, and keeps record of user access paths in a
fact table. As the click sequence and path traversal patterns represent the customer's theme,
these fi ndings could be translated into web site design and utilized to refi ne the web site
infrastructure. The refi nement of the web site design could generate much different patterns
of e-customer web pages click sequence. This phenomenon is a cyclic circle. To ensure
timeliness, our OLAM method takes a dynamic mining approach for most updated analysis,
by providing continued refi nement according to the change of the web site environment.
However, the problem exists of how to synchronize the update of the based relations with
the update of the view. This chapter offers a frame model metadata to facilitate the trigger
event, which is invoked whenever an incremental update occurs in the based relation, i.e.,
access log. The frame model metadata consist of data operation, which is used to update
the user access path. As a result, with OLAM, we can transform the data warehousing into
an active data warehousing which can activate the incremental data update from the based
relation into an existing view, after update during time interval.
The discovery of e-customer click sequence and profi le can help in designing a cus-
tomer-focused web site in the following ways:
1.
Make web site functionality intuitive by restructuring it around e-customers' preferred
surfi ng routes and processes. The popular web pages with the most diversifi ed pre-
requisite sequences and longest surfi ng time can be identifi ed and refi ned appropriately
with their page content and infrastructure.
2.
The isolated and inactive web pages imply that browsers are either incapable of access
to it or simply not interested enough to arouse a click. Further analysis on these web
page content and their dynamic links are necessary to decide upon whether metaphor
on web sites is necessary.
3.
Relate utilities
1
to relevant customer actions by easily accessible and visible utilitarian
components.
The future direction is to enhance our methodology with association rules established
between the UID in the end result click sequence patterns and the UID associated attributes
such as the user's personal particulars, for more association semantics discovery. The discov-
ery of targeted customers' personal online preference and offl ine particulars is an important
source for Customer Relationship Management (CRM) to build customer-oriented web sites
in the future as follows:
1.
Since web log data provide information about what kind of users will access what
kind of web pages, web log information can be integrated with web content and web
linkage structure mining to help web page ranking, web document classifi cation, and
the construction of a multi-layered web information base as well.
2.
Sequential pattern mining algorithms tend to generate a huge number of sequences.
At any given time, not all of those are of interest to the user. For example, a market-
ing analyst may only be interested in the activity of those online customers who have
visited certain pages in a specifi c time period. In general, discovered patterns must
meet certain rules and conditions. As a result, certain constraints must be integrated
with the web mining techniques to get a more reasonable and desired knowledge.
