The week's pick
Reseach Article
An Efficient Text Clustering Approach using Biased Affinity Propagation
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 96 - Number 1 |
| Year of Publication: 2014 |
| Authors: Isha Sharma, Mahak Motwani |
10.5120/16755-6273
|
Isha Sharma, Mahak Motwani . An Efficient Text Clustering Approach using Biased Affinity Propagation. International Journal of Computer Applications. 96, 1 ( June 2014), 1-4. DOI=10.5120/16755-6273
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.
References
- Shifei Ding and Hui Li "Quotient Space Granularity Selection Based A?nity Propagation Clustering Algorithm", Journal of Computational Information Systems 10: 6 (2014) 2425–2433
- Erik Cambria, Bjo?rn Schuller, Yunqing Xia and Catherine Havasi "New Avenues in Opinion Mining and Sentiment Analysis", Knowledge-Based approaches toconcept-level sentiment analysis.
- Chen Yang and Renchu Guan "A Feature-Metric-Based Affinity Propagation Technique for Feature Selection in Hyper-spectral Image Classification", Geoscience and Remote Sensing Letters, IEEE,Sept. 2013.
- Qingyao Wu, Michael K. Ng and Yunming Ye "Co-Transfer Learning Using Coupled Markov Chains withRestart", IEEE Intelligent Systems, 08 March 2013. IEEE computer Society Digital Library.
- Wei Chen, Qichong Tian, Xiaorong Jiang, Zhibo Tang, Caihua Guo, Xinzheng Xu, Hong Zhuand Shifei Ding "Domain Knowledge Blended Af?nity Propagation", Appl. Math. Inf. Sci. 7, No. 2, 717-723 (2013).
- Vicenc Quera, FrancescS. Beltran, InmarE. Givoni and Ruth Dolado "Determining shoal membership using affnity propagation", Behavioural Brain Research 241 (2013) 38–49.
- Stevan Rudinac, Alan Hanjalic and Martha Larson "Generating Visual Summaries of Geographic AreasUsing Community-Contributed Images", IEEE TRANSACTIONS ON MULTIMEDIA, VOL. 15, NO. 4, JUNE 2013.
- Teng Li,Bin Cheng, Xinyu Wu and Jun Wu "Low-Rank Affinity Based Local-Driven Multilabel Propagation", Mathematical Problems in EngineeringVolume 2013, Article ID 323481.
- Renchu Guan, Xiaohu Shi, Maurizio Marchese, Chen Yang, and Yanchun Liang "Text Clustering with Seeds Affinity Propagation", IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 23, NO. 4, APRIL 2011.
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