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Search Results: 1 - 10 of 1533 matches for " Jitendra Agrawal "
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Centroid Based Text Clustering
Priti Maheshwari,Jitendra Agrawal
International Journal of Engineering Science and Technology , 2010,
Abstract: Web mining is a burgeoning new field that attempts to glean meaningful information from natural language text. Web mining refers generally to the process of extracting interesting information and knowledge from unstructured text. Text clustering is one of the important Web mining functionalities. Text clustering is the task in which texts are classified into groups of similar objects based on their contents. Current research in the area of Web mining is tacklesproblems of text data representation, classification, clustering, information extraction or the search for and modeling of hidden patterns. In this paper we propose for mining large document collections it is necessary to pre-process the web documents and store the information in a data structure, which is more appropriate for further processing than a plain web file. In this paper we developed a php-mySql based utility to convert unstructured web documents into structured tabular representation by preprocessing, indexing .We apply centroid based web clustering method on preprocessed data. We apply three methods for clustering. Finally we proposed a method that can increase accuracy based on clustering ofdocuments.
Enhancing the Performance of Symmetric Key Cryptography Schema
Rupali Mehta,Prof. Jitendra Agrawal
International Journal of Engineering Innovations and Research , 2012,
Abstract: In this paper we are introducing a high Performance Symmetric Key Cryptography Schema used to increase the performance of symmetric key encryption algorithms like DES increasing their security by using compression and splitting techniques and other enhancement points. In this schema, the performance enchased by dividing data of into smaller equal parts. Then each parts is subjected to compressed
Comparative Performance of Arm and Farm on a Normalised Datasets
Prachi Singh Thakur,Jitendra Agrawal
International Journal of Computer Technology and Applications , 2011,
Abstract: Association rule mining is basically used to generate association rules on a real life datasets. A well-known algorithm called apriori is used to generate the frequent pattern itemsets for a given transaction. Since real life dataset consist of nominal, continuous, integer attribute fields, to convert it into binary format some type of pre-processing has to be done on the dataset.In this paper, we had evaluated the performance of two algorithms that is ARM(Association Rule Mining) and FARM(Fuzzy Association Rule Mining) on the basis of generation time by supplying different support and confidence values.for data pre-processing ,two methods are used: discretisation and normalisation. Discretisation converts the range of possible values of continuous data into subranges which is identified by a unique integer label .It also convert values associated with instances to corresponding integer label. Normalisation process converts values of nominal data into corresponding integer labels.
Optimization of Association Rule Mining through Genetic Algorithm
RUPALI HALDULAKAR,,Prof. JITENDRA AGRAWAL
International Journal on Computer Science and Engineering , 2011,
Abstract: Strong rule generation is an important area of data mining. In this paper we design a novel method for generation of strong rule. In which a general Apriori algorithm is used to generate the rules after that we use the optimization techniques. Genetic algorithm is one of the best ways to optimize the rules .In this direction for the optimization of the rule set we design a new fitness function that uses the concept ofsupervised learning then the GA will be able to generate the stronger rule set.
GA Optimized Negative Association Rule Mining
Sanjeev Sharma,Sudhir Sharma,Jitendra Agrawal
International Journal of Soft Computing , 2012,
Abstract: This study discusses the use of genetic algorithm in mining negative association rules. In general the rule generated by Association Rule Mining technique do not consider the negative occurrences of attributes in them, but by using Genetic Algorithms (GAs) over these rules the system can predict the rules which contains negative attributes. GA is used for this kind of knowledge discovery because of their ability to search globally and perform well in case of attributes interaction. Their strength is essentially due to updating of the whole population, consisting of normal case of individuals and worst case of individuals of the possible solution in an adaptive way.
Indigenous coated needle for nerve block
Kothari Dilip,Agrawal Jitendra,Mehrotra Amrita
Indian Journal of Anaesthesia , 2011,
Abstract:
Orbital involvement in tuberculosis
Agrawal P,Nath Jitendra,Jain B
Indian Journal of Ophthalmology , 1977,
Abstract:
Genetic counselling in prevention of blindness
Pratap V,Lal H,Agrawal Jitendra
Indian Journal of Ophthalmology , 1984,
Abstract:
Hydatid cyst of the orbit
Agrawal P,Agarwal Jitendra,Kala Priti
Indian Journal of Ophthalmology , 1982,
Abstract:
Dynamic adaptive routing algorithm based on ant algorithm in combination with queuing network analysis
Megha Singh,Jitendra Agrawal,Sanjeev Sharma
International Journal of Computer Science Issues , 2012,
Abstract: The field of Mobile Ad hoc Networks (MANETs) has expanded an important part of the interest of researchers, hence become very accepted in last few years. The main method for evaluating the performance of MANETs is simulation. This research study introduces a new adaptive and dynamic routing algorithm for MANETs based on the Ant Colony Optimization (ACO) algorithms with network delay analysis. Ant colony optimization algorithm helps in finding, if not the shortest, at least a very good path connecting the colony nest with a source of food. This evaluation of MANETs is based on the estimation of the mean End-to-End delay to send a packet from source to destination node through a MANET. The most important performance evaluation metrics in computer networks is evaluated as mean End-to-End delay. We scrutinize various simulation set-ups with different node density and pause times. Our new algorithm offers good results under certain conditions such as, increasing the pause time and decreasing node density.
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