The main goal of recommendation systems is to offer items to a particular user based on some factors, such as users' interests and preferences, thus allowing for more efficient information access. This paper descr...
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The explosive growth of mobile data demand is becoming an increasing burden on current cellular *** address this issue,we propose a solution of opportunistic data offloading for alleviating overloaded cellular *** pri...
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The explosive growth of mobile data demand is becoming an increasing burden on current cellular *** address this issue,we propose a solution of opportunistic data offloading for alleviating overloaded cellular *** principle behind it is to select a few important users as seeds for data *** three critical steps are detailed as *** first explore individual interests of users by the construction of user profiles,on which an interest graph is built by Gaussian graphical *** then apply the extreme value theory to threshold the encounter duration of user ***,a contact graph is generated to indicate the social relationships of ***,a contact-interest graph is developed on the basis of the social ties and individual interests of *** on different graphs,three strategies are finally proposed for seed selection in an aim to maximize overloaded cellular *** evaluate the performance of our algorithms by the trace data of real-word *** demonstrates the effectiveness of the strategy of taking social relationships and individual interests into account.
High-resolution X-ray computed tomography (CT) is the standard for pulmonary imaging. Depending on the scanner hardware, CT can provide high spatial and high temporal resolution, excellent contrast resolution for the ...
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Using migrating crawling agents (migrants) based methods, selection and filtration of web documents can be done at web servers rather than search engine side. It helps in reducing the network load significantly, cause...
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The features selection for machine learning models requires careful consideration. A good selection of features can enable machine learning models to better identify patterns in data and make more accurate predictions...
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Discovering the hierarchical structures of differ- ent classes of object behaviors can satisfy the requirements of various degrees of abstraction in association analysis, be- havior modeling, data preprocessing, patte...
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Discovering the hierarchical structures of differ- ent classes of object behaviors can satisfy the requirements of various degrees of abstraction in association analysis, be- havior modeling, data preprocessing, pattern recognition and decision making, etc. In this paper, we call this process as associative categorization, which is different from classical clustering, associative classification and associative cluster- ing. Focusing on representing the associations of behaviors and the corresponding uncertainties, we propose the method for constructing a Markov network （MN） from the results of frequent pattern mining, called item-associative Markov net- work （IAMN）, where nodes and edges represent the frequent patterns and their associations respectively. We further dis- cuss the properties of a probabilistic graphical model to guar- antee the IAMN＇s correctness theoretically. Then, we adopt the concept of chordal to reflect the closeness of nodes in the IAMN. Adopting the algorithm for constructing join trees from an MN, we give the algorithm for IAMN-based associa- tive categorization by hierarchical bottom-up aggregations of nodes. Experimental results show the effectiveness, efficiency and correctness of our methods.
The impact of personality styles on individuals' behavior and choices is undeniable. With the advancements in datamining and machine learning techniques, various methods have been proposed to automatically identif...
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More than three branches of death due to cardiovascular disease. Myocardial infarction (MI) is one of the most dangerous forms of coronary heart disease, with the highest mortality rate among other types of coronary h...
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Emergency message (EM) dissemination is a significant process in vehicular ad hoc networks (VANETs) and plays a vital role in road safety. Nonetheless, EMs’ dissemination while avoiding broadcast storms poses a consi...
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Based on the multiple wedge effects, a petal-shaped capsule robot(PCR) is proposed, and the self-centering phenomenon of the PCR is discovered. For investigating the self-centering characteristics, an innovative conce...
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Based on the multiple wedge effects, a petal-shaped capsule robot(PCR) is proposed, and the self-centering phenomenon of the PCR is discovered. For investigating the self-centering characteristics, an innovative concept of the instantaneous fluid membrane(FM) thickness, along with the dynamic FM thickness, is proposed; thus a dynamic FM thickness model and a hydrodynamic pressure(HP) model are derived when the PCR axis deviates from the pipe axis under the effect of gravity. A kinematics equation during suspending process in the vertical direction and a swimming kinematics equation in axial direction are derived respectively. Four capsule robots with different eccentricities of the tiles were manufactured and tested, the theoretical and experimental results show that the HP gradient is a fundamental reason for the self-centering phenomenon. The PCR with the self-centering ability can directly avoid the contact with the bottom of the gastrointestinal(GI) tract, achieving the excellent obstacle surmounting ability in the GI complex environment with the less twisted impact on the GI tract, which has a promising application prospect in the GI diagnosis.
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