The precise prediction of bus routes or the arrival time of buses for a traveler can enhance the quality of bus service. However, many social factors influence people's preferences for taking buses. These social f...
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Clustering is one of the effective ways to solve energy hole problem for Wireless Sensor network. So far, the approaches of heterogeneous cluster size mainly have concentrated on the design of unequal cluster protocol...
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Recent years have witnessed the growing popularity of hashing for efficient large-scale similarity search. It has been shown that the hashing quality could be boosted by hash function learning (HFL). In this paper, we...
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ISBN:
(纸本)9781577356332
Recent years have witnessed the growing popularity of hashing for efficient large-scale similarity search. It has been shown that the hashing quality could be boosted by hash function learning (HFL). In this paper, we study HFL in the context of multimodal data for cross-view similarity search. We present a novel multimodal HFL method, called Parametric Local Multimodal Hashing (PLMH), which learns a set of hash functions to locally adapt to the data structure of each modality. To balance locality and computational efficiency, the hashing projection matrix of each instance is parameterized, with guaranteed approximation error bound, as a linear combination of basis hashing projections of a small set of anchor points. A local optimal conjugate gradient algorithm is designed to learn the hash functions for each bit, and the overall hash codes are learned in a sequential manner to progressively minimize the bias. Experimental evaluations on cross-media retrieval tasks demonstrate that PLMH performs competitively against the state-of-the-art methods.
Mining frequent itemsets is a core problem in many data mining tasks, most existing works on mining frequent itemsets can only capture the long-term and static frequency itemsets, they do not suit the task whose frequ...
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MicroRNAs can regulate hundreds of target genes and play a pivotal role in a broad range of biological process. However, relatively little is known about how these highly connected miRNAs-target networks are remodelle...
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MicroRNAs can regulate hundreds of target genes and play a pivotal role in a broad range of biological process. However, relatively little is known about how these highly connected miRNAs-target networks are remodelled in the context of various diseases. Here we examine the dynamic alteration of context-specific miRNA regulation to determine whether modified microRNAs regulation on specific biological processes is a useful information source for predicting cancer prognosis. A new concept, Context-specific miRNA activity (CoMi activity) is introduced to describe the statistical difference between the expression level of a miRNA's target genes and non-targets genes within a given gene set (context).
This paper addresses the problem of Ranking Internet service quality by taking a machine learning approach using multiple service features. Ranking helps find good services for applications that use services as buildi...
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This paper addresses the problem of Ranking Internet service quality by taking a machine learning approach using multiple service features. Ranking helps find good services for applications that use services as buildi...
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This paper addresses the problem of Ranking Internet service quality by taking a machine learning approach using multiple service features. Ranking helps find good services for applications that use services as building blocks. Unlike other ranking problems, the goodness of Internet service qualities is dependent upon multiple key features. The key features vary across different service categories and have unequally discriminative natures. This paper divides the ranking problem into four subtasks including categorizing services according to the service functionalities, identifying key features that determine the quality, denoising for feature measurement values and computing global ranking scores with multiple key features, which are cast into machine learning problems and solved using techniques classification, feature selection, clustering, and regression respectively. In particular, we propose in this paper an efficient dense-block based denoising method for subjective features, and a Supported Vector Regression based method for computing global ranking scores. Experimental results on both synthetic and real data show that the proposed approach can quantitatively identify the key features across service categories, discard noisy measurement values in 10 times faster, and compute the global ranking scores using multiple features with low mean squared errors for both linear and nonlinear ranking functions.
It is a challenge to make the routes quickly adapt to the changed network topology when nodes fail in a wireless ad hoc *** this paper,we propose an adaptive routing protocol,which groups the network nodes into virtua...
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It is a challenge to make the routes quickly adapt to the changed network topology when nodes fail in a wireless ad hoc *** this paper,we propose an adaptive routing protocol,which groups the network nodes into virtual nodes according to their data transfer capabilities and creates virtual-node-based *** protocol can accommodate the routes to node failures by adaptively updating the virtual nodes and just-in-time using available nodes during data *** simulations indicate that the proposed protocol can keep the routes failed-node-free when the available virtual node members cover the failed nodes scattering area.
Machine vision is an active branch of Artificial Intelligence. An important problem in this area is the balance among efficiency, accuracy and huge computing. The visual system of human can keep watchfulness to the pe...
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Machine vision is an active branch of Artificial Intelligence. An important problem in this area is the balance among efficiency, accuracy and huge computing. The visual system of human can keep watchfulness to the perimeter of visual field while at same time their central attention is focused to the center of visual field for fine information processing. This mechanism of computing resource assignment could ease the demand for huge and complex hardware structure. Therefore designing computer model based on biological visual
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