Image annotation is a challenging problem due to the rapid growing of real world image archives. In this paper, we propose a novel approach to the solving of this problem based on a variant of the support vector clust...
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Image annotation is a challenging problem due to the rapid growing of real world image archives. In this paper, we propose a novel approach to the solving of this problem based on a variant of the support vector clustering (SVC) algorithm, i.e., the support vector description of clusters. The system has two major components, the training process and the annotating process. In the training process, clusters of image manually annotated by descriptive words are used as training instances. Each cluster is described by a one-cluster SVC model. The proposed model can exploit the advantage of SVC for its ability to delineate cluster boundaries of arbitrary shape. Moreover, the training process of the one-cluster SVC model is formulated as the process of building density estimator for underlying distribution of the cluster. In the annotating process, for a test image, the probability of this instance being generated by each model is computed. And then the relevant words are selected based on the obtained probabilities. Simulated experiments were conducted on the Corel60k data set. The results demonstrate the performance of the proposed algorithm, compared with the performance of other algorithms.
Most contemporary database systems query optimizers exploit System-R's bottom-up dynamic programming method (DP) to find the optimal query execution plan (QEP) without evaluating redundant subplans. The distinguis...
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Among those researches in Deep Web, compared to research of data extraction which is more mature, the research of data annotation is still at its preliminary stage. Currently, although the approach of applying ontolog...
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Automatic image annotation is a promising solution to narrow the semantic gap between low-level content and high-level semantic concept, which has been an active research area in the fields of image retrieval, pattern...
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作者：
Wei DuZhongbo CaoYan WangEnrico BlanzieriChen ZhangYanchun LiangCollege of Mathematics
Jilin University Changchun 130012 China Department of Information and Communication Technology University of Trento Povo 38050 Italy College of Computer Science and Technology
Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun 130012 China College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun 130012 China
Deep web could automatically produce web pages according to the query criteria of users. The report found most query result page store data information using table form. Knowledge management, information retrieval, We...
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Deep web could automatically produce web pages according to the query criteria of users. The report found most query result page store data information using table form. Knowledge management, information retrieval, Web mining, abstract extraction and so on were benefited from automatically understanding of table forms. The study web forms on the web information extraction and integration have important significance. This paper proposed a domain-specific ontology based strategy for integration tables, and this method could independent the structure of table. Experimental results confirm that this method could effectively improve the accuracy of integration.
Image retrieval has been an active research topic due to its great importance in the field of image management, digital library and web searching. However, the performances of the existing approaches, including text-b...
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This paper introduces a qualitative spatial model based on previously developed models for representation and reasoning the spatial information described in natural language. The model is integrated with direction and...
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lti-label learning aims at predicting a proper label set for each unseen *** instance in the dataset is associated with a set of predefined ***-label learning approaches frequently used choose identical feature set to...
lti-label learning aims at predicting a proper label set for each unseen *** instance in the dataset is associated with a set of predefined ***-label learning approaches frequently used choose identical feature set to determine the instance's membership of each label.
Integrity constraint is a formula that checks whether all necessary information has been explicitly provided. It can be added into ontology to guarantee the data-centric application. In this paper,a set of constraint ...
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Integrity constraint is a formula that checks whether all necessary information has been explicitly provided. It can be added into ontology to guarantee the data-centric application. In this paper,a set of constraint axioms called IC-mapping axioms are stated. Based on these axioms,a special ontology with integrity constraint,which is adapted to map ontology knowledge to data in relational databases,is defined. It＇s generated through our checking and modification. Making use of the traditional mapping approaches,it can be mapped to relational databases as a normal ontology. Unlike what in the past,a novel mapping approach named IC-based mapping is proposed in accordance with such special ontology. The detailed algorithm is put forward and compared with other existing approaches used in Semantic Web applications. The result shows that our method is advanced to the traditional approaches.
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