Micro-blog,also known as twitter,is a platform which is based on user relationships for information sharing,spreading and *** how to share the messages in micro-blog efficiently based on the users' interest with a...
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Micro-blog,also known as twitter,is a platform which is based on user relationships for information sharing,spreading and *** how to share the messages in micro-blog efficiently based on the users' interest with analyzing the user information has become a key research *** to the analysis of the micro-blog user relationship and the theory of Analytic Hierarchy Process in the management science,this paper establishes a user influence model,to help explain how the target users affect the core *** the combination of Word Activation Forces Theory,we put forward an algorithm to express the emotional tendentious of each noun-word in all the *** addition,we calculate and find the corresponding tweets to recommend to the core user and the experiment in this paper proves the effectiveness of the algorithm.
This paper proposes a new framework of band selection for object classification in hyperspectral images. Different from traditional approaches where the selected bands are shared from all classes, in this work, differ...
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ISBN:
(纸本)9781467322164
This paper proposes a new framework of band selection for object classification in hyperspectral images. Different from traditional approaches where the selected bands are shared from all classes, in this work, different subsets of bands are selected for different class pairs. Without prior knowledge of spectral database, we estimate the spectral characteristic of objects with the labeled and unlabeled samples, benefiting from the concept of semi-supervised learning, Under the assumption of Gaussian mixture model (GMM), the vectors of mean values and covariance matrices for each class are estimated. The separabilities for all pairs of classes are thus calculated on each band. The bands with the highest separabilities are then selected. To validate our band selection result, support vector machine (SVM) is employed using a strategy of one against one (OAO). Experiments are conducted on a real data set of hyperspectral image, and the results can validate our algorithm.
Automatically facial expression recognition(FER) has become more and more important today,making machine understand human's emotion by expression having various potential applications,especially in the field of hu...
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Automatically facial expression recognition(FER) has become more and more important today,making machine understand human's emotion by expression having various potential applications,especially in the field of human machine interaction(HCI).But FER still remains a challenge problem in computer vision as the subtleness of facial expression is difficult to capture and the robustness of the recognition in various situation is also hard to *** this paper,a Gabor wavelet and structured sparse representation based classification(SSRC) are proposed aiming to solve the FER *** Gabor wavelet filter is used to extract the subtle facial expression,and the structured sparse representation based classification(SSRC) is used for classifying the test images *** sparse representation based classification(SRC),the SSRC explicitly takes structure of the dictionary into account for a better *** results show the better performance of our proposed method compared with other traditional methods,especially more robust in case of facing corruption or occlusion.
In the topic search system,some of web pages got by crawling are inconsistent with user *** this situation,this paper had a research on content-based web filtering *** paper proposed a dual feature selection method ba...
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In the topic search system,some of web pages got by crawling are inconsistent with user *** this situation,this paper had a research on content-based web filtering *** paper proposed a dual feature selection method based on the CHI statistical method and N-gram,and then made binary text classification by SVM in order to achieve Web *** experiments showed that the proposed web filtering method has better results.
ANFIS is a fuzzy inference system integrated into neural networks normally used for patternrecognition and classification *** this work,an ANFIS was designed and used to predict preclinical performance of medical stu...
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ANFIS is a fuzzy inference system integrated into neural networks normally used for patternrecognition and classification *** this work,an ANFIS was designed and used to predict preclinical performance of medical students based on given *** inputs included academic achievements during preclinical,pre-university,and high *** most significant predictors were found to be a combination of performances across the *** of the prediction was measured in terms of the Root Mean Square *** results were as robust as of the linear ***,the ANFIS model is a good alternative predictive tool.
Multiple Outlooks Learning (MOL) has recently received considerable attentions in machine learning. While traditional classification models often assume patterns are living in a fixed-dimensional vector space, MOL foc...
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Recent developments of Human-Computer Interaction (HCI) technologies allow for a natural integration of car drivers in their vehicle environments. Using a driving assisting system based on HCI interfaces novice driver...
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Recent developments of Human-Computer Interaction (HCI) technologies allow for a natural integration of car drivers in their vehicle environments. Using a driving assisting system based on HCI interfaces novice drivers can interact naturally in various driving situations and they can develop skills and abilities. One of the novelties of our on-going driving assistant project is represented by a multi-tracking HCI system based on a set of markerless sensors. In this paper we present how the proposed system enables us to recognize novice driver postures in various driving situations. Unlike previous approaches we do not consider body postures alone, but in relation with the following cues: eyes and head dynamics and contextual environmental information, i.e., states of the car and traffic information about driving situations. We built a rule-based expert system for driving posture detection that uses inputs from the data fusion of sensors. By analyzing the sequence of postures we can assess if the novice drivers maneuvers are performed in a correct manner and order, in relation to the car driving skills. The feasibility of the proposed system is verified through experiments. Results show that driver postures are recognized with an average of 96.43% accuracy and that car driver skills are enhanced using the proposed system.
In recent years,crowdsourcing has become an effective method in many fields,such as relevance evaluation of search engine ***,the problems of bad workers and quality control always stand among the major challenges wit...
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In recent years,crowdsourcing has become an effective method in many fields,such as relevance evaluation of search engine ***,the problems of bad workers and quality control always stand among the major challenges within the *** on our experiments carried out in TREC 2011 Crowdsourcing track,this paper demonstrates a realtime strategy in recruiting workers and monitoring the quality of their relevance and rank *** effectiveness of our strategy has been verified by empirical results.
As to the live performance sound and studio recording sound recognition,a comparison approach based on audio features is proposed in this paper,which utilizes preprocessing of the audio information,audio features extr...
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As to the live performance sound and studio recording sound recognition,a comparison approach based on audio features is proposed in this paper,which utilizes preprocessing of the audio information,audio features extraction,dynamic time warping(DTW) in order to capture the characteristic difference between the live performance sound and studio recording *** results show the high performance to distinguish these two types of audio sounds by applying the proposed method.
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