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Comparison of Swarm Intelligence Techniques for Improved Information Retrieval System
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 129 - Number 10 |
| Year of Publication: 2015 |
| Authors: Priyanka J. Howale, Sanketa S. Pradhan, Shraddha G. Lohar, Mehul D.Redekar, Anagha N. Chaudhari |
10.5120/ijca2015907016
|
Priyanka J. Howale, Sanketa S. Pradhan, Shraddha G. Lohar, Mehul D.Redekar, Anagha N. Chaudhari . Comparison of Swarm Intelligence Techniques for Improved Information Retrieval System. International Journal of Computer Applications. 129, 10 ( November 2015), 39-42. DOI=10.5120/ijca2015907016
Abstract
Optimization is an important and critical step in the data mining process and it has a huge impact on the success of a data mining process. Selecting a set of feature which is optimal for a given task is a problem which plays an important role in a wide variety of context including pattern recognition, adaptive control and machine learning Clusters are formed of the reduced dataset using Swarm Intelligence Technique algorithms i.e. Particle Swarm Optimization(PSO),Ant Colony Optimization(ACO),Cluster Hypothesis is verified which is the intra cluster distance should be minimum and inter cluster distance should be maximum. Most relevant documents are stored i+n the clusters An Information Retrieval System is used for retrieval of data from the clusters. When user enters a query from a Graphical User Interface, using Information Retrieval algorithm the document is searched and retrieved from the clusters. It is then given as an output to the user
References
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