International Journals

Permanent URI for this collectionhttps://dspace.psgrkcw.com/handle/123456789/178

Browse

Author: search.filters.author.V, Pream Sudha

Search Results

Now showing 1 - 3 of 3
  • No Thumbnail Available
    Item
    UNSUPERVISED APPROACH FOR DOCUMENT CLUSTERING USING MODIFIED FUZZY C MEAN ALGORITHM
    (International Journal of Computer& Organization Trends, 2011-11) K, Sathiyakumari; V, Pream Sudha; G, Manimekalai
    Clustering is one the main area in data mining literature. There are various algorithms for clustering. There are several clustering approaches available in the literature to cluster the document. But most of the existing cluring techniques suffer from a wide range of limitations. The existing clustering approaches face the issues like practical applicability, very less accuracy, more classification time etc. In recent times, inclusion of fuzzy logic in clustering results in better clustering results. One of the widely used fuzzy logic based clustering is Fuzzy C-Means (FCM) Clustering. In order to further improve the performance of clustering, this thesis uses Modified Fuzzy C-Means (MFCM) Clustering. Before clustering, the documents are ranked using Term Frequency–Inverse Document Frequency (TF–IDF) technique. From the experimental results, it can be observed that the proposed technique results in better clustering results when compared to the existing technique
  • No Thumbnail Available
    Item
    A SURVEY ON VARIOUS APPROACHES IN DOCUMENT CLUSTERING
    (International Journal of Computer Technology and Application, 2011-09) K, Sathiyakumari; G, Manimekalai; V, Pream Sudha
    Document clustering is the process of segmenting a particular collection of texts into subgroups including content based similar ones. The purpose of document clustering is to meet human interests in information searching and understanding. Nowadays all paper documents are in electronic form, because of quick access and smaller storage. So, it is a major issue to retrieve relevant documents from the larger database. Text mining is not a standalone task that human analysts typically engage in. The goal is to transform text composed of everyday language in a structured, database format. In this way, heterogeneous documents are summarized and presented in a uniform manner. Among others, the challenging problems of document clustering are big volume, high dimensionality and complex semantics.
  • No Thumbnail Available
    Item
    A TREE BASED MODEL FOR HIGH PERFORMANCE CONCRETE MIX DESIGN
    (International Journal of Engineering Science and Technology, 2010-02) C, Deepa; K, Sathiyakumari; V, Pream Sudha
    Concrete is the sustainable construction material, which is most widely used in the world as it provides superior fire resistance, gains strength over time and gives an extremely long service life. Its annual consumption is estimated between 21 and 31 billion tones. The paper is aimed at guiding the selection of available materials and proportioning them as to produce the most economical concrete suitable for the desired purpose. According to the National Council for Cement and Building Materials (NCBM), New Delhi, the compressive strength of concrete is governed generally, by the water-cement ratio. The mineral admixtures like fly ash, ground granulated blast furnace, silica fume and fine aggregates also influence it. The main purpose of this paper is to find the accuracy for the compressive strength of high performance concrete by using classification algorithms like Multilayer Perceptron, Rnd tree models and C-RT regression. The result from this study suggests that tree based models perform remarkably well for designing the concrete mix.