Asian Science Citation Index is committed to provide an authoritative, trusted and significant information by the coverage of the most important and influential journals to meet the needs of the global scientific community.  
ASCI Database
308-Lasani Town,
Sargodha Road,
Faisalabad, Pakistan
Fax: +92-41-8815544
Contact Via Web
Suggest a Journal
Articles by V. SaiShanmuga Raja
Total Records ( 3 ) for V. SaiShanmuga Raja
  T. Muralidharan , V. Saishanmuga Raja and S.P. Rajagopalan
  In the most recent couple of years as internet utilization turns into the principle supply route of the life’s every day exercises, the issue of spam turns out to be intense for web group. Spam pages frame a genuine risk for a wide range of clients. This risk demonstrated to advance constantly with no piece of information to lessen. Diverse types of spam saw an emotional increment in both size and negative effect. A lot of e-mails and website pages are considered spam either in Simple Mail Transfer Protocol (SMTP) or web crawlers. Numerous specialized strategies were proposed to approach the issue of spam. We propose a Hybrid Extensive Machine Learning Algorithm (HEMLA) for detection and classification of that offers weight to the data nourished by clients and thinks about the presence of some space particular components. Hybrid extensive machine learning algorithm is a combination of many learning algorithms like conjugate gradient, resilient back-propagation and levenberg-marquardt algorithms. The outcomes demonstrate that the hybrid extensive machine learning algorithm overcomes the traditional web filtering methods as far as reducing the false positives and the false negatives and increasing the accuracy.
  D. Elantamilan , V. SaiShanmuga Raja and S.P. Rajagopalan
  In this research, we have presented a technique for individual recognizable proof in view of iris recognition utilizing genetic algorithm and neural network. The procedure of iris recognition comprises of confinement of the iris locale and area of information set of iris pictures took after by iris design recognition. A neural network is utilized to diminish the low recognition rate, low accuracy and expanded time of recuperation. Here, the genetic algorithm is utilized to upgrade the neural networks parameters. The reenactment comes about demonstrate a decent recognizable proof rate and lessened preparing time. The iris became a much-explored field. Human iris contains unique and very important information about persons.
  S. Jayasundar , V.N. Rajavarman and V. Saishanmuga Raja
  Keyword search is an efficient data retrieval method for the WWW, largely because the simple and efficient nature of keyword processing allows a large amount of information to be searched with fast response. However, keyword search methods do not formally capture the clear meaning of a keyword query and fail to address the semantic relationships between keywords. As a result, the accuracy (precision and recall rate) is often unsatisfactory and the ranking algorithms fail to properly reflect the semantic relevance of keywords. Our research particularly focuses on increasing the accuracy of search results for multi-word search. We propose a statistical ontology-based semantic ranking algorithm based on sentence units and a new type of query interface including wildcards.
Copyright   |   Desclaimer   |    Privacy Policy   |   Browsers   |   Accessibility