Web Text Clustering and Evaluation Algorithm Based on Fuzzy Set

Yun Peng; Hongxin Wan
January 2013
International Journal of Digital Content Technology & its Applic;Jan2013, Vol. 7 Issue 1, p11
Academic Journal
Because of uncertainty and non-structure of web text, it is very difficult to cluster the text by some normal classification methods. An algorithm of web text clustering based on fuzzy set is proposed, and the algorithm has been described in detail by example in this paper. The technique mentioned above can decrease the algorithm complexity of time and space, at the same time increase the robustness of clustering. In order to evaluate the clustering results, a fuzzy evaluation algorithm about elements of cluster is proposed. There are a lot of uncertain data in web text cluster, so the traditional method of evaluation to the incomplete data is very difficult. Evaluation algorithm based on fuzzy set can improve the reliability and accuracy of clustering evaluation. The process of clustering evaluating is described by example in detail.


Related Articles

  • Software Refactoring at the Class Level using Clustering Techniques. Alkhalid, Abdulaziz; Alshayeb, Mohammad; Mahmoud, Sabri A. // Journal of Research & Practice in Information Technology;Nov2011, Vol. 43 Issue 4, p285 

    Software becomes more and more complex as it adapts new requirements, is enhanced or is modified. Thus, the quality of the software decreases. Therefore, there is a need to reduce the software's complexity and improve its quality. Refactoring reduces software complexity and improves quality by...

  • Association rules optimization algorithm based on fuzzy clustering. Yu Fu; JunRui Yang // Applied Mechanics & Materials;2014, Issue 602-605, p3536 

    Frequent pattern mining has been an important research direction in association rules. This paper use a methodology by preprocessing the original dataset using fuzzy clustering which can mapped quantitative datasets into linguistic datasets. Then we propose a algorithm based on fuzzy frequent...

  • A Spatial Division Clustering Method and Low Dimensional Feature Extraction Technique Based Indoor Positioning System. Yun Mo; Zhongzhao Zhang; Weixiao Meng; Lin Ma; Yao Wang // Sensors (14248220);Jan2014, Vol. 14 Issue 1, p1850 

    Indoor positioning systems based on the fingerprint method are widely used due to the large number of existing devices with a wide range of coverage. However, extensive positioning regions with a massive fingerprint database may cause high computational complexity and error margins, therefore...

  • Agricultural Enterprise Internal Control Fuzzy Comprehensive Evaluation Research. Li Haicheng; Suo Zhilin // International Journal of Digital Content Technology & its Applic;Jan2013, Vol. 7 Issue 2, p661 

    In order to improve efficiency of agricultural enterprise, we study the problem of agricultural enterprise internal control. The fuzzy comprehensive evaluation method is introduced to agricultural enterprise internal control evaluation field. We study the process of fuzzy comprehensive...

  • A Novel Approach for PAM Clustering Method. Bin Al Abid, Faisal // International Journal of Computer Applications;Jan2014, Vol. 86, p1 

    Existing and in recent times proposed clustering algorithms are studied and it is known that the k-means clustering method is mostly used for clustering of data due to its reduction of time complexity. But the foremost drawback of k-means algorithm is that it suffers from sensitivity of outliers...

  • Hot topics found on micro-blog based on speed growth. XUE Su-zhi; LU Ran; REN Yuan-yuan // Application Research of Computers / Jisuanji Yingyong Yanjiu;Sep2013, Vol. 30 Issue 9, p2598 

    In hot topics found on micro-blog, because the text of micro-blog is short and less words, and the terms are not standard, so the traditional hot topic detection method can not find hot topics effectively. In order to solve this problem, this paper presented a method of hot topics found based on...

  • Agent for Documents Clustering using Semantic-based Model and Fuzzy. Fouad, Khaled M.; Hassan, Moataz O. // International Journal of Computer Applications;Jan2013, Vol. 61, Special section p10 

    Text clustering plays an important role in providing intuitive navigation and browsing mechanisms by organizing large sets of documents into a small number of meaningful clusters. Many fuzzy clustering algorithms, such as K-means, deal with documents as bag of words. The bag of words...

  • A COMPARATIVE ANALYSIS BETWEEN K-MEAN AND Y-MEANS ALGORITHMS IN FISHER'S IRIS DATA SETS. Leela, V.; Sakthi priya, K.; Manikandan, R. // International Journal of Engineering Science & Technology;Feb/Mar2013, Vol. 5 Issue 1, p245 

    Cluster analysis plays a vital role in various fields in order to group similar data from the available database. There are various clustering algorithm available in order to cluster the data but the entire algorithm are not suitable for all process .This paper mainly address with the...

  • MPBCA: Mobility Prediction Based Clustering Algorithm for MANET. Rani, V. G.; Punithavalli, M. // International Journal of Engineering Science & Technology;Feb/Mar2013, Vol. 5 Issue 1, p403 

    MANET is a multi hop wireless network in which the mobile nodes are dynamic in nature. Each node in the network has a limited bandwidth and minimum battery power. Due to this challenging environment the mobile nodes can be grouped to achieve better stability. Grouping the mobile nodes is called...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics