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Broadcasting message via the social web, people always hope that the message goes through the most credible path, and would like to know trustworthiness on the most credible path and the least credible path. To solve these problems, this article defines the concepts related to the most credible path and the least credible path for single-source broadcast. Proposes algorithms on the most credible path...
Adding semantic annotation for Web page is the foundation on constructing semantic Web. Lexical patterns based annotation methods are adopted by most of the semantic annotation systems. The structures and visual features of Web pages imply valuable semantic information, such as relation between entities, but these features are often ignored by current semantic annotation methods. A hybrid pattern...
Semantic information has been paid much attention in web IR. Although many researches have improved the retrieval performance by employing WordNet synset and concept, relations between concepts are often ignored by most of the semantic retrieval methods. We propose a relation enhanced concept vector model CRVM(concept-relation vector model) for document representation in this paper, and the documents...
In many applications including network monitoring, Web click stream analysis, sensor networks, detection of network intrusions, telecommunications data management and financial applications, data arrives in a stream fashion. The main focus in algorithms for data streams has been on efficient construction of synopsis data structures. This paper introduces the problem of construction of synopsis data...
Many data stream sources are prone to dramatic spikes in volume, and data items arrive in a bursting fashion. Peak load during a spike can be orders of magnitude higher than typical load, and processing all the arrived data items will exceed memory availability. It becomes necessary to shed load by dropping some fraction of the unprocessed data items during a spike. We consider the problem of load...
Detecting tumor in mammography is a difficult task because of complexity in the image. This brings the necessity of creating automatic tools to find whether a mammography present tumor or not. In this paper we integrate neural network with reduction of rough set theory which we call the rough neural network (RNN) to classify digital mammography. The experimental results show that the RNN performs...
There are growing interests in algorithms for processing and querying continuous data streams recently. This paper introduces the problem of sampling from landmark windows over data streams and presents a weighted stratified multistage sampling (WSMS) algorithm for this problem. The algorithm extends the classic reservoir-sampling algorithm and the weighted sampling algorithm with a reservoir by using...
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