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An Efficient Text Clustering Approach using Biased Affinity Propagation
| Content Provider | CiteSeerX |
|---|---|
| Author | Sharma, Isha Motwani, Mahak |
| Abstract | Based on an effective clustering algorithm Seeds affinity propagation- in this paper an efficient clustering approach is presented which uses one dimension for the group of the words representing the similar area of interest with that we have also considered the uneven weighting of each dimension depending upon the categorical bias during clustering. After creating the vector the clustering is performed using seeds-affinity clustering technique. Finally to study the performance of the presented algorithm, it is applied to the benchmark data set Reuters-21578 and compared it for F-measure, with k-means algorithm and the original AP (affinity propagation) algorithm the results shows that the presented algorithm outperforms the others by acceptable margin. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Efficient Text Clustering Approach Biased Affinity Propagation Presented Algorithm Benchmark Data Seeds-affinity Clustering Technique Affinity Propagation Acceptable Margin Original Ap Uneven Weighting Similar Area K-means Algorithm Categorical Bias Efficient Clustering Approach |
| Content Type | Text |
| Resource Type | Article |
