Deepak Khemani

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In this paper, an evolutionary programming-based clustering algorithm is proposed. The algorithm effectively groups a given set of data into an optimum number of clusters. The proposed method is applicable for clustering tasks where clusters are crisp mad spherical. This algorithm determines the number of clusters and the cluster centers in such a way that(More)
Most of the real life classification problems have ill defined, imprecise or fuzzy class boundaries. Feedforward neural networks with conventional backpropagation learning algorithm are not tailored to this kind of classification problem. Hence, in this paper, feedforward neural networks, that use backpropagation learning algorithm with fuzzy objective(More)
The task of planning in a dynamic and uncertain domain is considerably more challenging than in domains traditionally adopted by classical planning methods. Planning in real situations has to be 8 knowiedp intm ptoceu, particudarly since it is not easy to predict all the effects of one’s actions. However, many knowledge bated implementations are susceptible(More)
Textual-case based reasoning (TCBR) systems where the problem and solution are in free text form are hard to evaluate. In the absence of class information, domain experts are needed to evaluate solution quality, and provide relevance information. This approach is costly and time consuming. We propose three measures that can be used to compare alternate TCBR(More)
Clusters of text documents output by clustering algorithms are often hard to interpret. We describe motivating real-world scenarios that necessitate reconfigurability and high interpretability of clusters and outline the problem of generating clusterings with interpretable and reconfigurable cluster models. We develop a clustering algorithm toward the(More)
This paper describes a CBR application in manufacturing industry, a domain where CBR has by and large proved its applicability and success. The paper details a thorough understanding of the field of fused cast manufacturing basically seen from the perspective of glass furnace, where quality of glass produced is straightaway related to the refractory blocks(More)
This paper illustrates the utility of URL information in unsupervised learning. We outline the motivation behind the usage of URL information upfront, and present two techniques for unsupervised learning from URL corpora. First, we devise a similarity measure for URL pairs putting down the intuitions behind the same and verify its goodness by using it for(More)