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The all-pairs-similarity-search (or similarity join) problem has been extensively studied for text and a handful of other datatypes. However, surprisingly little progress has been made on similarity joins for time series subsequences. The lack of progress probably stems from the daunting nature of the problem. For even modest sized datasets the obvious nested-loop algorithm can take months, and the...
In this paper, we tackle the problem of common object (multiple classes) discovery from a set of input images, where we assume the presence of one object class in each image. This problem is, loosely speaking, unsupervised since we do not know a priori about the object type, location, and scale in each image. We observe that the general task of object class discovery in a fully unsupervised manner...
Cancer tissues in histopathology images exhibit abnormal patterns; it is of great clinical importance to label a histopathology image as having cancerous regions or not and perform the corresponding image segmentation. However, the detailed annotation of cancer cells is often an ambiguous and challenging task. In this paper, we propose a new learning method, multiple clustered instance learning (MCIL),...
As the Web contains rich and convenient information, Web search engine is increasingly becoming the dominant information retrieving approach. In order to rank the query results of web pages in an effective and efficient fashion, we propose a new page rank algorithm based on similarity measure from the vector space model, called SimRank, to score web pages. Firstly, we propose a new similarity measure...
In this paper, the necessity of ranking of the enterprise's informatization capacity maturity is researched on the basis of EICMM (Enterprise Informatization Capacity Maturity Model). Based on the EICMM, we adopt the proper method (Cluster Analytical Method) for the empirical research, commence from the evaluated index system, design the questionnaires and collect the related data of informatization,...
K-means clustering is widely used due to its fast convergence, but it is sensitive to the initial condition.Therefore, many methods of initializing K-means clustering have been proposed in the literatures. Compared with Kmeans clustering, a novel clustering algorithm called affinity propagation (AP clustering) has been developed by Frey and Dueck, which can produce a good set of cluster exemplars...
The prosperous development of the customer to customer business has made trust and distrust salient. In this background, a key question is how trust and distrust propagate themselves among people who do not have previous interactions with each other, yet little research has been conducted towards this ending. Therefore, this paper attempts to fill the research gap by studying the propagation of trust...
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