Conference Papers
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Item Ontology based algorithms for indexing and search of semantically close natural language phrases(2007) Kamath S․, S.Free text constitutes a overwhelming fraction of information available on the World Wide Web. Specifically, consider small chunks of natural language phrases frequently used by Web users to describe stuff relevant to them. For example, consider the following two posts on a classifieds site (which serves a small locality, say, a university campus) - "2 Tickets for the prom tonight" and "Trade 2 extra passes for tonight's Ball for $25". For a human looking at these two posts, its trivial to conclude that he has found what he wanted. But when there are thousands of such posts and in the absence of any common keywords or any additional information from the user it is unlikely that naive keyword based matching will be of any help in reflecting the glaring similarity between these descriptions. This problem is very relevant and challenging because users tend to describe the same item in several dif ferent ways. Humans frequently use their commonsense and background knowledge to infer that these relate to the same item. However the enormous sizes of most datasets prohibit manual classification. To automate this, we present intuitive and scalable algorithms which use existing Ontologies like WordNet to correctly relate semantically close descriptions.Item Performance evaluation of web browsers in Android(2013) Harsha Prabha, E.; Piraviperumal, D.; Naik, D.; Kamath S․, S.; Prasad, G.In this day and age, smart phones are fast becoming ubiquitous. They have evolved from their traditional use of solely being a device for communication between people, to a multipurpose device. With the advent of Android smart phones, the number of people accessing the Internet through their mobile phones is on a steep rise. Hence, web browsers play a major role in providing a highly enjoyable browsing experience for its users. As such, the objective of this paper is to analyze the performance of five major mobile web browsers available in the Android platform. In this paper, we present the results of a study conducted based on several parameters that assess these mobile browsers' functionalities. Based on this evaluation, we also propose the best among these browsers to further enrich user experience of mobile web browsing along with utmost performance. © 2013 Springer Science+Business Media New York.Item A prototype of an intelligent search engine using machine learning based training for learning to rank(Springer Science and Business Media Deutschland GmbH info@springer-sbm.com, 2014) Rai, P.; Prabhumoye, S.; Khattri, P.; Sandhu, L.S.; Kamath S․, S.Learning to Rank is a concept that focuses on the application of supervised or semi-supervised machine learning techniques to develop a ranking model based on training data. In this paper, we present a learning based search engine that uses supervised machine learning techniques like selection based and review based algorithms to construct a ranking model. Information retrieval techniques are used to retrieve the relevant URLs by crawling the Web in a Breadth-First manner, which are then used as training data for the supervised and review based machine learning techniques to train the crawler. We used the Gradient Descent Algorithm to compare the two techniques and for result analysis. © Springer International Publishing Switzerland 2014.Item NLP based intelligent news search engine using information extraction from e-newspapers(Institute of Electrical and Electronics Engineers Inc., 2014) Kanakaraj, M.; Kamath S․, S.Extracting text information from a web news page is a challenging task as most of the E-News content is provided with support from backend Content Management Systems (CMSs). In this paper, we present a personalized news search engine that focuses on building a repository of news articles by applying efficient extraction of text information from a web news page from varied e-news portals. The system is based on the concept of Document Object Model(DOM) tree manipulation for extracting text and modifying the web page structure to exclude irrelevant content like ads and user comments. We also use WordNet, a thesaurus of English language based on psycholinguist studies for matching the extracted content semantically to the title of the web page. TF-IDF (Term Frequency Inverse Document Frequency) is used for identifying the web page blocks carrying information relevant to the pages title. In addition to the extraction of information, functionalities to gather related information from different web news papers and to summarize the gathered information based on user preferences have also been included. We observed that the system was able to achieve good recall and high precision for both generalized and specific queries. © 2014 IEEE.Item An equal share ant colony optimization algorithm for job shop scheduling adapted to cloud environments(Springer Verlag service@springer.de, 2014) Chaukwale, R.; Kamath S․, S.The problem of efficiently scheduling jobs on several machines is an important consideration for Cloud computing. Task scheduling in Cloud Environment is a recognised NP-hard problem and hence methods that focus on producing an exact solution can prove insufficient in finding an optimal resolution to JSSP. Hence, in such cases, heuristic methods can be employed to find a good solution within reasonable time. In this paper, we study the conventional ACO algorithm and propose two Load Balancing ACO algorithms for task scheduling in Cloud Environment. We also present the observed results, and discuss them with reference to the FCFS scheduling algorithm currently used. It is observed that the proposed algorithm gives better results for every problem size. Also the proposed algorithms are adapted and applied to Task scheduling in Cloud Environment and is found to give better results. © 2014 Springer International Publishing Switzerland.Item Similarity analysis of service descriptions for efficient Web service discovery(Institute of Electrical and Electronics Engineers Inc., 2014) Kamath S․, S.; Ananthanarayana, V.S.Web services are currently one of the preferred ways for realizing Service Oriented Architectures in business systems. Due to this popularity and also due partly to the failure of the Universal Business Registry initiative, the number of published service descriptions openly available on the Web has increased by a large extent and hence, relevant service discovery as per user specification remains a challenge. In order to achieve more efficient discovery, we propose a crawler based system for gathering service descriptions available on the Web for building a scalable service repository. We apply similarity analysis techniques to the service descriptions after extracting features provided by the service descriptions and automatically generate relevant tags for each service. Using Agglomerative Hierarchical clustering, we cluster the tagged service descriptions and use the same tagging technique to generate tags for each cluster. For generating cluster tags, we take into account how well the tag represents the corresponding service in the cluster and how well the service itself represents the cluster it is in. The search domain for service discovery was significantly reduced by tagging & clustering and and we show that our system achieves good results. © 2014 IEEE.Item An hybrid bio-inspired task scheduling algorithm in cloud environment(Institute of Electrical and Electronics Engineers Inc., 2014) Madivi, R.; Kamath S․, S.Cloud computing is currently a very popular computing paradigm as it provides ubiquitous, on-demand access as a service to computing resources via the Internet. In spite of offering marked advantages over the traditional style of computing, there are several issues related to load on the computing system and task scheduling to outperform the computation that need to be effectively solved in order to provide better quality of service to the service consumer. Task scheduling is a crucial research area since it affects the system load and performance; and there will always be scope for optimizing existing scheduling algorithms and propose efficient new task scheduling algorithms. Many task scheduling algorithms to resolve this problem have already been proposed - Particle Swarm Optimization, Ant Colony Optimization, Genetic algorithms, Artificial Bee Algorithm etc. In this paper, we propose a hybrid task scheduling algorithm that is based on combining the plus points of bio-inspired algorithms like Ant Colony Optimization and Artificial Bee Algorithm. We show were the strong points of both these algorithms can be utilized and incorporated in order to optimize task scheduling in the cloud algorithm. It is observed that the proposed algorithm gave an improvement of about 19% when compared to the default FCFS scheduling strategy, 11% better than ABC algorithm and performed 9% better than the conventional ACO based task scheduling. © 2014 IEEE.Item An hybrid bio-inspired task scheduling algorithm in clouds environment(Institute of Electrical and Electronics Engineers Inc., 2014) Madivi, R.; Kamath S․, S.Cloud computing is currently a very popular computing paradigm as it provides ubiquitous, on-demand access as a service to computing resources via the Internet. In spite of offering marked advantages over the traditional style of computing, there are several issues related to load on the computing system and task scheduling to outperform the computation that need to be effectively solved in order to provide better quality of service to the service consumer. Task scheduling is a crucial research area since it affects the system load and performance; and there will always be scope for optimizing existing scheduling algorithms and propose efficient new task scheduling algorithms. Many task scheduling algorithms to resolve this problem have already been proposed - Particle Swarm Optimization, Ant Colony Optimization, Genetic algorithms, Artificial Bee Algorithm etc. In this paper, we propose a hybrid task scheduling algorithm that is based on combining the plus points of bio-inspired algorithms like Ant Colony Optimization and Artificial Bee Algorithm. We show were the strong points of both these algorithms can be utilized and incorporated in order to optimize task scheduling in the cloud algorithm. It is observed that the proposed algorithm gave an improvement of about 19% when compared to the default FCFS scheduling strategy, 11% better than ABC algorithm and performed 9% better than the conventional ACO based task scheduling. © 2014 IEEE.Item Comparative analysis of Vertex Cover computation algorithms for varied graphs(Institute of Electrical and Electronics Engineers Inc., 2014) Patel, S.; Kamath S․, S.There are several vertex cover algorithms proposed for the solution of well-known NP-complete class problem of computing vertex cover. The Vertex Cover problem is important to address as it has various real world applications viz. Wireless Communication Network, Airline Communication Network, Terrorist Communication Network, etc. In this paper, we present a comparative evaluation of different existing algorithms like approximation, list, greedy and Alom's for most efficiently computing vertex cover over a variety of large graphs. Our empirical study found that Alom's algorithm performs consistently better than the other algorithms for all types of graphs, regardless of their class and number of vertices in the graph, while approximation algorithms show the worst performance for very large graphs. © 2014 IEEE.Item Improved approximation algorithm for vertex cover problem using articulation points(Institute of Electrical and Electronics Engineers Inc., 2014) Patel, S.; Kamath S․, S.There has been many vertex cover algorithms proposed for the solution of well-known NP-complete class problem of vertex cover. The Vertex Cover problem is important to address in graphs as it has various real world applications viz. Wireless Communication Network, Airline Communication Network, Terrorist Communication Network etc. In this paper, we propose a new algorithm based on Articulation Point, which reduces the vertex cover computation problem in polynomial time and yield solution nearer to an optimal solution, better than the classical approach. We also present a Graphical Visualization Tool that allows the automatic application of the Improved Articulation Point based Approximation Algorithm to process large graphs and finds their articulation points for minimal vertex cover computation. The tool is currently under development.