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Heterogeneous social networks present a great challenge for link mining tasks and especially for link prediction. Recent work insists on the importance of information heterogeneity intelligent exploitation in order to achieve best results. That will be more possible only with the development of new techniques that may represent heterogeneous network in an effective way making it possible to simplify...
Sentence similarity compute is an important part in question answering system based on frequency asking questions. The accuracy of the existing sentence similarity algorithm needs to be improved, so this paper presents a revised question similarity compute method. We combine the word order feature with vector space model algorithm. When we use the VSM to compute the question similarity, we propose...
Playing a vital role, saliency has been widely applied for various image analysis tasks, such as content-aware image retargeting, image retrieval and object detection. It is generally accepted that saliency detection can benefit from the integration of multiple visual features. However, most of the existing literatures fuse multiple features at saliency map level without considering cross-feature...
Automatic detection of the human emotion is an important area in computer science and psychology to develop adaptive Human-Computer Interaction (HCI). In this paper, a novel approach is proposed to extract a user's pleasure during English comprehension. The approach is based on processing the mouse movement data during the interaction with the system and determining whether or not the user enjoys...
Nowadays consumers can obtain abundant information for products and service from online review resources, which can help them make decisions. Moreover, it motivates some manufactures to hire spammers writing fake reviews on some target products. How to detect spam review/reviewer is drawing more and more attention of e-commerce. In this paper, we construct a novel multi-edge graph model in which each...
A new probability-based parsing model DPSK (Dependency Parsing with Structure Knowledge) is presented for dependency parsing. Similar to a bottom-up chart parsing algorithm, DPSK select the best dependency arc between two words in a sentence according to the probability. The arc probability depends on two kinds of information: (1) Features extracting from two words of the arc. (2) Features extracting...
Group abnormal behaviors often occur abruptly under video surveillance, thus bringing serious consequences. How to recognize these behaviors correctly has always been the difficulty in research on intelligence video surveillance. This paper is based on the basic theory of Markov Random Fields to extract the features of those in video images, so as to recognize the group abnormal behaviors under video...
Saliency detection has been a very active research area in recent years. Most traditional methods suffer from the problem that existing visual features are not discriminative or not robust enough to predict salient locations. As a result, the experimental results of these previous methods are still far from satisfactory. In this paper, we propose to utilize a two-layer Deep Boltzmann Machine (DBM)...
When one is speaking, lips change regularly. Therefore, Lip contour extraction is very meaningful. In this paper, for lip color images, this paper extracts lip contour by means of the RGB-based improved region growing algorithm. Through RGB three components, the relationship between color from and adjacent pixels is calculated. According to certain rules, seed pixels are automatically selected, and...
Attacks such as XSS and SQL injections are still common in browser extensions due to the presence of potential vulnerabilities in extensions and some extensions are also malicious by design. As a consequence, much effort in the past has been spent on detecting vulnerable and malicious browser extensions. These techniques are limited to only detect either new forms of vulnerable or malicious extensions...
At present, computer graphics is widely used in various aspects in our daily life. Hence the course is becoming more and more essential, while many students don't know how to study this course, their interests are lost because of awful grades. So how to learn computer graphics is essential now. This paper introduces a method, which is a progressive method on studying and practicing of computer graphics.
The RLS-MARS (Regularized Least Squares-Multi Angle Regression and Shrinkage) feature selection model is used to select the relevant information, in which both, the keeping and the leaving-out of the regularizer are present. The RLS-MARS model is to find a series of directions in multidimensional space, leading the gradient vectors to change along those directions which would make the gradient matrix's...
Features have been widely used in the field of domain engineering to model commonality and variability among a family of related systems. In order to obtain a precise feature model and make sure that each element in the feature model establishes its reason for existing, we propose a trace ability approach to constructing domain feature model from use case models. In this approach, a domain use case...
As the demands for Classification of the images is getting higher and higher, users want to search the images more fast and precisely, so a kind of fuzzy decision tree algorithm was presented, which was used to set up a images' emotion classification tree based on the image emotion which had a higher precision. This algorithm is based on the uncertainty of Classification using in images' emotion classification...
While many process mining algorithms have been proposed recently, there does not exist a widely-accepted benchmark to evaluate and compare these process mining algorithms. As a result, it can be difficult to choose a suitable process mining algorithm for a given enterprise or application domain. Some recent benchmark systems have been developed and proposed to address this issue. However, evaluating...
This paper presents a dedicated approach to detect loop closures using visually salient patches. We introduce a novel, energy maximization based saliency detection technique which has been used for unsupervised landmark extraction. We explain how to learn the extracted landmarks on-the-fly and re-identify them. Furthermore, we describe the sparse location representation we use to recognize previously...
In this paper, we propose a novel approach for object detection via foreground feature selection and part-based shape model. It automatically learns a shape model from cluttered training images without need to explicitly given bounding box on objects. Our approach commences by extracting a set of feature descriptors, and iteratively selects the foreground features using Earth Movers Distances based...
In this paper, we import the Cognitive Biases to the field of music generation, and point out its merit. We adopt the Loosely Symmetric (LS) Model based on human illogical biases of cognition, which includes the symmetric bias and the mutual exclusivity bias, as a melody generation. We regard features of melodies as the simplest sequence of transitional events from preceding note to succeeding note...
The goal of this work is to estimate the spatial extents of complex geospatial objects such as high schools and golf courses. Gazetteers are deficient in that they currently specify the spatial extents of these objects using a single latitude/longitude point. We propose a framework that uses readily available high resolution overhead imagery to estimate the boundaries of known object instances in...
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