Web usage mining using artificial ant colony clustering and linear genetic programming

@article{Abraham2003WebUM,
  title={Web usage mining using artificial ant colony clustering and linear genetic programming},
  author={Ajith Abraham and Vitorino Ramos},
  journal={The 2003 Congress on Evolutionary Computation, 2003. CEC '03.},
  year={2003},
  volume={2},
  pages={1384-1391 Vol.2}
}
  • A. Abraham, Vitorino Ramos
  • Published 8 December 2003
  • Computer Science
  • The 2003 Congress on Evolutionary Computation, 2003. CEC '03.
The rapid e-commerce growth has made both business community and customers face a new situation. Due to intense competition on the one hand and the customer's option to choose from several alternatives, the business community has realized the necessity of intelligent marketing strategies and relationship management. Web usage mining attempts to discover useful knowledge from the secondary data obtained from the interactions of the users with the Web. Web usage mining has become very critical… 

WEB USAGE MINING USING NEURAL NETWORK

TLDR
A novel approach Growing Neural Gas is introduced kind of neural network, in the process of Web Usage Mining to detect user’s patterns, and details the transformations necessaries to modify the data storage in the Web Servers Log files to an input of GNG.

A Novel Approach for web usage mining using Growing Neural Gas

TLDR
A novel approach Growing Neural Gas is introduced kind of neural network, in the process of Web usage mining, which provides models of distributed adaptive organization, which are useful to solve difficult optimization, classification, and distributed control problems, among others.

APPLYING ARTIFICIAL NEURAL NETWORK IN WEB USAGE MINING

TLDR
A novel approach Growing Neural Gas is introduced kind of neural network, in the process of Web Usage Mining to detect user’s patterns, which provides models of distributed adaptive organization, which are useful to solve difficult optimization, classification, and distributed control problems, among others.

An Improved Hybrid Algorithm for Web Usage Mining

TLDR
A combination of hierarchical user emotion analysis and a self-organizing mapping algorithm in the training and testing of a recommended system that identifies the least dissimilar element, which will not last, and prefers the highest priority element in the cluster.

A Result Evolution Approach for Web usage mining using Fuzzy C-Mean Clustering Algorithm

TLDR
A novel approach FCM Algorithm is introduced kind of Clustering Technique, in the process of Web Usage Mining to detect user’s patterns, and it is shown that the efficiency of FCMAlgorithm is better than k-mean algorithm for web log data.

Cluster optimization for enhanced web usage mining using fuzzy logic

  • N. M. VargheseJ. John
  • Computer Science
    2012 World Congress on Information and Communication Technologies
  • 2012
TLDR
Fuzzy Cluster-chase algorithm for cluster optimization is presented to personalize web page clusters of end users to eliminate the redundancies occur in data after clustering done by web usage mining methods.

A Survey on Swarm and Evolutionary Algorithms for Web Mining Applications

TLDR
This paper focuses mainly on the web data and proposes some conceptual theories to extract knowledge through different web mining techniques like Clustering,FIS,ANN,LGP etc and Swarm Intelligence techniques which are based on distributive self organized system are discussed.

A Comparative Study of Rule Mining Based Web Usage Mining Algorithms

TLDR
This work compares the two standard web usage mining algorithms namely Apriori algorithm and Frequent Pattern algorithm and focused on discovering the web usage patterns of websites from the server log files.

A Review: Study of various Ant Colony Optimization Techniques

TLDR
Some Ant Colony Clustering and optimization technique for Web server log file to analyze user's interest, which is useful for giving suggestion about specific user’s interest are concerned.

Evolutionary Computation in Intelligent Network Management

TLDR
This chapter presents two real world applications where evolutionary computation has been used to solve network management problems and investigates the suitability of linear genetic programming technique to model fast and efficient intrusion detection systems.
...

References

SHOWING 1-10 OF 27 REFERENCES

i-Miner: a Web usage mining framework using hierarchical intelligent systems

  • A. Abraham
  • Computer Science
    The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ '03.
  • 2003
TLDR
A novel approach 'intelligent-miner' (i-Miner) is introduced to optimize the concurrent architecture of a fuzzy clustering algorithm (to discover data clusters) and a fuzzy inference system to analyze the trends, which is efficient with lesser number of if-then rules and improved accuracy at the expense of complicated algorithms and extra computational cost.

Soft Computing Paradigms for Web Access Pattern Analysis

TLDR
Empirical results clearly demonstrate that the proposed SCPs could predict the hourly and daily Web traffic volume and the developed TSFIS gave the overall best performance compares with other proposed paradigms.

Web mining research: a survey

TLDR
This paper surveys the research in the area of Web mining, point out some confusions regarded the usage of the term Web mining and suggest three Web mining categories, which are then situate some of the research with respect to these three categories.

Web usage mining: discovery and applications of usage patterns from Web data

TLDR
A detailed taxonomy of the work in this area, including research efforts as well as commercial offerings is provided, and a brief overview of the WebSIFT system as an example of a prototypical Web usage mining system is given.

LumberJack: Intelligent Discovery and Analysis of Web User Traffic Composition

TLDR
This paper describes the further development of this work into a prototype service called LumberJack, a push-button analysis system that is both more automated and accurate than past systems.

Web page clustering using a self-organizing map of user navigation patterns

Identification of Web User Traffic Composition using Multi-Modal Clustering and Information Scent

TLDR
This paper introduces and describes a method to discover major types of information goals of Web surfers automatically using multi-modal vectors that encompass various sources of information, including Content, Topology, and URL.

Self-Organized Stigmergic Document Maps: Environment as a Mechanism for Context Learning

TLDR
The present ant clustering system (ACLUSTER) avoids not only short-term memory based strategies, as well as the use of several artificial ant types, present in some recent approaches, and is also the first application of ant systems into textual document clustering.

Warehousing and mining Web logs

TLDR
A relational OLAP (ROLAP) approach for creating a web-log warehouse is described, populated both from web logs, as well as the results of mining web logs.

Creating adaptive Web sites through usage-based clustering of URLs

TLDR
An effective technique for capturing common user profiles based on association rule discovery and usage based clustering is proposed and techniques for combining this knowledge with the current status of an ongoing Web activity to perform real time personalization are proposed.