Marching Cubes is the most frequently used method to reconstruct isosurface from a point cloud. However, the point clouds are getting denser and denser, thus the efficiency of Marching cubes method has become an obsta...
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Wireless sensor network is now becoming a burgeoning distributed computing paradigm which resembles traditional wireless ad hoc network in some aspects such as network organization. However, wireless sensor network di...
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This paper presents a semi-naive classifier named RoughTree, which is designed to alleviate the attribute interdependence problem of Naive Bayesian Classifier. RoughTree uses the attribute dependence detecting measure...
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Retrieval-based methods have been proven effective in many NLP tasks. Previous methods use representations from the pre-trained model for similarity search directly. However, the sentence representations from the pre-...
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The current P2P application protocols are usually constructed over the application-level overlay network. However, because the users in the P2P systems always follow a very dynamic mode, the overlay network with poor ...
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The online reviews are one type of social media which are opinions generated by the users to comment on some special items. Since the sentiments are dependent on topics, probabilistic topic models have been widely use...
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Semantic segmentation is an important task in medical image analysis. In general, training models with high performance needs a large amount of labeled data. However, collecting labeled data is typically difficult, es...
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In this report, we mainly present an overview of ObjectCoref, which follows a self-training framework to resolve object coreference on the Semantic Web. Besides, we show preliminary results of Falcon-AO (2010) for thi...
In this report, we mainly present an overview of ObjectCoref, which follows a self-training framework to resolve object coreference on the Semantic Web. Besides, we show preliminary results of Falcon-AO (2010) for this year's OAEI campaign, including the benchmark and conference tracks.
It is well-known that the values of symbolic variables may take various forms such as an interval, a set of stochastic measurements of some underlying patterns or qualitative multi-values and so on. However, the major...
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It is well-known that the values of symbolic variables may take various forms such as an interval, a set of stochastic measurements of some underlying patterns or qualitative multi-values and so on. However, the majority of existing work in symbolic data analysis still focuses on interval values. Although some pioneering work in stochastic pattern based symbolic data and mixture of symbolic variables has been explored, it still lacks flexibility and computation efficiency to make full use of the distinctive individual symbolic variables. Therefore, we bring forward a novel hierarchical clustering method with weighted general Jaccard distance and effective global pruning strategy for complex symbolic data and apply it to emitter identification. Extensive experiments indicate that our method has outperformed its peers in both computational efficiency and emitter identification accuracy.
Nowadays, attackers seek various covert channels to access the users’ privacy on the mobile devices. Recent research has demonstrated that the built-in motion sensors can be exploited to monitor the users’ screen ta...
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