A SimRank based Ensemble Method for Resolving Challenges of Partition Clustering Methods

323–327Traditional clustering techniques alone cannot resolve all challenges of partition-based clustering methods. In the partition based clustering, particularly in variants of K-means, initial cluster centre selection is a significant and crucial point. The dependency of final cluster is totally based on initial cluster centres; hence, this process is delineated to be most significant in the entire clustering operation. The random selection of initial cluster centres is unstable, since different cluster centre points are achieved during each run of the algorithm. Ensemble based clustering methods resolve challenges of partition-based methods. The clustering ensembles join several partitions generated by different clustering algorithms into a single clustering solution. The proposed ensemble methodology resolves initial centroid problems and improves the efficiency of cluster results. This method finds centroid selection through overall mean distance measure. The SimRank based similarity matrix find that the bipartite graph helps to ensemble

A SimRank based Ensemble Method for Resolving Challenges of Partition Clustering Methods

Traditional clustering techniques alone cannot resolve all challenges of partition-based clustering methods. In the partition based clustering, particularly in variants of K-means, initial cluster centre selection is a significant and crucial point. The dependency of final cluster is totally based on initial cluster centres; hence, this process is delineated to be most significant in the entire clustering operation. The random selection of initial cluster centres is unstable, since different cluster centre points are achieved during each run of the algorithm. Ensemble based clustering methods resolve challenges of partition-based methods. The clustering ensembles join several partitions generated by different clustering algorithms into a single clustering solution. The proposed ensemble methodology resolves initial centroid problems and improves the efficiency of cluster results. This method finds centroid selection through overall mean distance measure. The SimRank based similarity matrix find that the bipartite graph helps to ensemble

How hybrids manage growth and social–business tensions in global supply chains: the case of impact sourcing

This study contributes to the growing interest in how hybrid organizations manage paradoxical social–business tensions. Our empirical case is ‘‘impact sourcing’’— hybrids in global supply chains that hire staff from disadvantaged communities to provide services to business clients. We identify two major growth orientations— ‘‘community-focused’’ and ‘‘client-focused’’ growth—their inherent tensions and ways that hybrids manage them. The former favors slow growth and manages tensions through highly integrated client and community relations; the latter promotes faster growth and manages client and community relations separately. Both growth orientations address social–business tensions in particular ways, but also create latent constraints that manifest when entrepreneurial aspirations conflict with the current growth path. In presenting and discussing our findings, we introduce preempting management practices of tensions, and the importance of geographic embeddedness and distance to the paradox literature

A Comparison of the Industrialization Paths for Asian Services Outsourcing Industries, and Implications for Poverty Alleviation

This paper examines three software and/or information technology enabled services (ITES) industries - two in the early stages of development (in the People's Republic of China [PRC] and the Philippines) and one mature one (in India). Being latecomers to offshoring work, the PRC and the Philippines have developed this industry in cooperation with multinational enterprises (MNEs). PRC firms have worked with and upgraded within MNEs' value chains within the PRC market, while the Philippines has relied on MNEs to come in and set up facilities, with domestic firms setting up facilities where lower (knowledge) barriers to entry prevail. The paper also explores the ITES industries' implications for economic growth and poverty reduction. ITES industries can contribute to overall economic growth and exports, but due to their small size, will generally tend to have more observable impacts on the cities in which they are located. From the limited case data available, it appears that the ITES industries impact on overall employment and other economic sectors to varying degrees, relative to other sectors. As these industries do not help the more impoverished or less educated, they cannot be said to be a solution for the less employable or impoverished, let alone to the problem of rural poverty

Unstructured Data: Qualitative Analysis

Major research is taking place in analyzing and processing of massive amounts of data produced by different organizations. The lumps of data received must be stored and different techniques are needed to visualize the numerical statistics. We have to focus on factors related to performance levels. This paper provides big data disaster management and different admission policy techniques to analyze the performance based on socio-economic factors and educational achievements along with comparison of admission policies