18,016 research outputs found
A Survey on Web Usage Mining
Now a day World Wide Web become very popular and interactive for transferring of information. The web is huge, diverse and active and thus increases the scalability, multimedia data and temporal matters. The growth of the web has outcome in a huge amount of information that is now freely offered for user access. The several kinds of data have to be handled and organized in a manner that they can be accessed by several users effectively and efficiently. So the usage of data mining methods and knowledge discovery on the web is now on the spotlight of a boosting number of researchers. Web usage mining is a kind of data mining method that can be useful in recommending the web usage patterns with the help of users2019; session and behavior. Web usage mining includes three process, namely, preprocessing, pattern discovery and pattern analysis. There are different techniques already exists for web usage mining. Those existing techniques have their own advantages and disadvantages. This paper presents a survey on some of the existing web usage mining techniques
A Survey on Web Usage Mining
Now a day World Wide Web become very popular and interactive for transferring of
information. The web is huge, diverse and active and thus increases the scalability, multimedia data
and temporal matters. The growth of the web has outcome in a huge amount of information that is
now freely offered for user access. The several kinds of data have to be handled and organized in a
manner that they can be accessed by several users effectively and efficiently. So the usage of data
mining methods and knowledge discovery on the web is now on the spotlight of a boosting number
of researchers. Web usage mining is a kind of data mining method that can be useful in
recommending the web usage patterns with the help of users’ session and behavior. Web usage
mining includes three process, namely, preprocessing, pattern discovery and pattern analysis.
There are different techniques already exists for web usage mining. Those existing techniques have their own advantages and disadvantages. This paper presents a survey on some of the existing web usage mining techniques
Binary Particle Swarm Optimization based Biclustering of Web usage Data
Web mining is the nontrivial process to discover valid, novel, potentially
useful knowledge from web data using the data mining techniques or methods. It
may give information that is useful for improving the services offered by web
portals and information access and retrieval tools. With the rapid development
of biclustering, more researchers have applied the biclustering technique to
different fields in recent years. When biclustering approach is applied to the
web usage data it automatically captures the hidden browsing patterns from it
in the form of biclusters. In this work, swarm intelligent technique is
combined with biclustering approach to propose an algorithm called Binary
Particle Swarm Optimization (BPSO) based Biclustering for Web Usage Data. The
main objective of this algorithm is to retrieve the global optimal bicluster
from the web usage data. These biclusters contain relationships between web
users and web pages which are useful for the E-Commerce applications like web
advertising and marketing. Experiments are conducted on real dataset to prove
the efficiency of the proposed algorithms
WEB MINING IN E-COMMERCE
Recently, the web is becoming an important part of people’s life. The web is a very good place to run successful businesses. Selling products or services online plays an important role in the success of businesses that have a physical presence, like a reE-Commerce, Data mining, Web mining
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