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Ontology, the base of Semantic Web, plays a vital role in knowledge representation and knowledge reasoning. There are many tools providing management interfaces to create, query and edit knowledge of ontology. However, most of them are still arduous time-consuming manual work. Therefore, how to automatically construct ontology has attracted many researchers' attention. With the development of WEB,...
Large numbers of cavities formed by underground mining endangers the mine's safety seriously and generates much difficulty for the resource reclamation in domestic mines. Therefore, taking advanced Cavity Monitoring System (CMS) as basic mean, carrying out correlative technologies research and application to overcome these problems in the underground metal mines has become a significant task. The...
The sign of unknown input coefficients is assumed to be known in most papers about the input uncertainties. In this paper, a Nussbaum gain method is adopted to cope with the situation that both the sign and the value of input are unknown. And the unknown parameters can be estimated under the situation of unknown sign of control. At last, numerical simulations are done to show the effectiveness of...
In Automatic Question Answering System, topic identification is usually based on relevancy computation of sentences. This paper introduces an approach to compute topic relevancy. Using the semantic computation in HowNet, the relevancy of sentences can be calculated. The topic relevancy of sentences can be calculated through the computation of relevancy between words of sentence and subject words....
Ontology is applied to a real-world Web intelligent question answering system in PC troubleshooting domain as an improvement, so semantic relations need to be extracted to construct ontology semi-automatically. The paper mainly pays attention to "product-trouble" relation and "product-attribute" relation. A two stage semantic relation extraction method is proposed. In stage one,...
Mammography is currently regarded as one of the best ways to detect breast cancer in the early stage. However, due to the limitation in imaging condition and the subtleness of the difference between normal and abnormal features, it is generally difficult to interpret the mammograms. Thus, image enhancement techniques have been widely used in screening mammograms. In this paper, a multiscale contrast...
Landmark labeling of training images is essential for many learning tasks in computer vision, such as object detection, tracking, and alignment. Image labeling is typically conducted manually, which is both labor-intensive and error-prone. To improve this process, this paper proposes a new approach to estimate a set of landmarks for a large image ensemble with only a small number of manually labeled...
Local Feature Extraction (LFE) algorithm is an effective feature extraction method developed in recent years. One of the shortcomings of the current LFE algorithm is that it can only process labeled data, and does not work well when the amount of the labeled data is limited. However, it is usually easy to obtain large amount of unlabeled data but only a few labeled data. In this paper, we propose...
The wavelet/scalar quantization (WSQ) [1] fingerprint image compression algorithm is effective and has been widely applied to fingerprint image compression. However, WSQ cannot control the compression ratio and its performance on fuzzy images is poor. We propose an improved WSQ fingerprint image compression algorithm to overcome the above shortcomings. Our algorithm uses a mixed quantizer so that...
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