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Aim of this paper is to find out shortest path navigation route to reach nearest required location. With increasing development in society the structure of the road networks are more complicated and finding the shortest path in such network is difficult one. Some situations where we need quick response and shorter path to reach to the destination. In emergency situation selecting a wrong path may...
Content Based Image Retrieval is one of the most promising method for image retrieval where searching and retrieving images from large scale image database is a critical task. In Content Based Image Retrieval many visual feature like color, shape, and texture are extracted in order to match query image with stored database images. Matching the query image with each image of large scale database results...
Data Mining is an efficient data analysis process which is used to find the patterns and relationship of a large database. Clustering is a popular technique of data mining for unsupervised learning in which labels are not defined previously. K-Mean is a well known partitioning technique for forming different clusters, but it has the drawback of initial sensitivity and local optima convergence. K-Harmonic...
Clustering is an unsupervised technique, which partitions the entire input space into regions. These initial partitions have a great impact on the resulting clusters. In this paper, a new Multi Stage Genetic Clustering (MSGC) scheme for multiobjective optimization in data clustering is proposed, which can automatically partition the data into an appropriate number of clusters. K-means is a well-known...
Cluster analysis is an important step in data mining. For clustering, various multiobjective techniques are evolved, which can automatically partition the data into an appropriate no. of clusters. K-means is a well known data clustering algorithm and is proven to be better for many practical applications. The proposed work is based on achieving multiple objective functions for data clustering thereby,...
This article presents a new Unification Matching Scheme (UMS) for information retrieval using the genetic algorithm. The selection of appropriate matching functions contributes to the performance of the information retrieval system. The proposed UMS executes the Unification function on three classical matching functions for different threshold values. The main objective is to utilize all the base...
This article presents a novel information retrieval algorithms using genetic algorithm to increase the performance of information retrieval system. The novel matching functions called Overall Matching Function (OMF) and Virtual Center based Matching Function (VCF) are proposed for improving the retrieval performance. Overall Matching Function gives the results by finding the average of matching scores...
Clustering is the process of organising data into meaningful groups, and these groups are called clusters. It is a way of grouping data samples together that is similar in some way, according to some criteria that you pick. Swarm intelligence (SI) is a collective behavior of social systems like insects such as ants (ant colony optimization, ACO), fish schooling, honey bees (bee algorithm, BA) and...
In this paper, we propose a method of genetic algorithm (GA) for information retrieval (IR) based on Singular Value Decomposition and Principal Component Analysis. The main difficulty in GA based IR system is processing of high dimensional input strings, as affects the performance in terms of retrieval time. In proposed work, we tried to reduce the high dimensional input data to low dimensional in...
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