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Review links are widely used in some special kinds of web pages, especially news pages. They are very useful pieces of information in many applications, such as hot topic discovery and public opinion monitoring. Unfortunately, extracting review links manually from news pages is time-consuming and error-prone. Though lots of works on web data extraction have been developed, we argue that this is still...
Inductive transfer learning and semi-supervised learning are two different branches of machine learning. The former tries to reuse knowledge in labeled out-of-domain instances while the later attempts to exploit the usefulness of unlabeled in-domain instances. In this paper, we bridge the two branches by pointing out that many semi-supervised learning methods can be extended for inductive transfer...
While the intrusion detection system in network is making great progress, it is also facing great challenges. The applications of data mining technique in computer security field improve the development of EDS. It is necessary to classify the attack degrees in IDS and use it in IDS by data mining. In spite of IDS can detect the attack activities in network, the result is uncertain. To describe the...
A new inductive transfer-learning algorithm called NEDRT is presented in this paper in order to improve the classification accuracy of a domain task by using the knowledge learned from labeled data generated from a different domain. NEDRT introduces a novel error function for a constructed neural network by summing a weighted squared difference between the real output and the neural network output...
In this paper, a novel learning method based on kernelized fuzzy clustering and least squares support vector machines (LSSVM) is presented to improve the generalization ability of a Takagi-Sugeno-Kang (TSK) fuzzy modeling. Firstly, the fuzzy partition of the product space of input and output is obtained by kernelized fuzzy clustering. Then, a computationally efficient numerical method is proposed...
In order to overcome the dimension problem of the traditional fuzzy clustering, we use kernel-based fuzzy c-means clustering (KFCM) to construct first-order TSK fuzzy models. The proposed algorithm is composed of two phases. In the first phase, the antecedent fuzzy sets are obtained by KFCM. We present the expression of the cluster prototypes of KFCM with different kernel functions in original input...
This paper presents an algorithm based on the method of supervised machine learning and multi-keyframes to achieve markerless augmented reality (AR) application when there is a locally planar object in the scene. The main goal is to solve the problem of AR tracking in outdoor environment by only using vision and natural features. Instead of tracking fiducial markers, we track natural keypoints, during...
Energy efficiency is an important issue in wireless sensor networks. One available power saving strategy is having only a portion of nodes work, but this would always compromise data quality as a result. In this paper, we propose an adaptive nodes scheduling approach (ADNS) to conserve energy while maintaining the overall data quality. ADNS selects a subset of nodes to be active and puts the others...
Road information understanding is a necessary task for both intelligent vehicles and driving assistance systems. Previous research mostly focused on the detection of lane position. Other information provided by arrow markings was scarcely mentioned. In this paper, Arrow extraction is carried out by projection histogram on Inverse perspective image and an arrow markings recognition algorithm is presented...
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