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【期刊论文】Partition-Based Block Matching of Large Class Hierarchies
瞿裕忠, Wei Hu, Yuanyuan Zhao, and Yuzhong Qu
ASWC 2006, LNCS 4185, pp. 72-83, 2006.,-0001,():
-1年11月30日
Ontology matching is a crucial task of enabling interoperation betweenWeb applications using different but related ontologies. Due to the size and the monolithic nature, large-scale ontologies regarding real world domains cause a new challenge to current ontology matching techniques. In this paper, we propose a method for partition-based block matching that is practically applicable to large class hierarchies, which are one of the most common kinds of large-scale ontologies. Based on both structural affinities and linguistic similarities, two large class hierarchies are partitioned into small blocks respectively, and then blocks from different hierarchies are matched by combining the two kinds of relatedness found via predefined anchors as well as virtual documents between them. Preliminary experiments demonstrate that the partitionbased block matching method performs well on our test cases derived from Web directory structures.
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【期刊论文】Finding Important Vocabulary Within Ontology
瞿裕忠, Xiang Zhang, Hongda Li, and Yuzhong Qu
ASWC 2006, LNCS 4185, pp. 106-112, 2006.,-0001,():
-1年11月30日
In current Semantic Web community, some researches have been done on ranking ontologies, while very little is paid to ranking vocabularies within ontology. However, finding important vocabularies within a given ontology will bring benefits to ontology indexing, ontology understanding and even ranking vocabularies from a global view. In this paper, Vocabulary Dependency Graph (VDG) is proposed to model the dependencies among vocabularies within an ontology, and Textual Score of Vocabulary (TSV) is established based on the idea of virtual documents. And then a Double Focused PageRank algorithm is applied on VDG and TSV to rank vocabulary within ontology. Primary experiments demonstrate that our approach turns out to be useful in finding important vocabularies within ontology.
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【期刊论文】FalconAO: Aligning Ontologies with Falcon
瞿裕忠, Ningsheng Jian, Wei Hu, Gong Cheng, Yuzhong Qu
,-0001,():
-1年11月30日
Falcon-AO is an automatic tool for aligning ontologies. There are two matchers integrated in Falcon-AO: one is a matcher based on linguistic matching for ontologies, called LMO; the other is a matcher based on graph matching for ontologies, called GMO. In Falcon-AO, GMO takes the alignments generated by LMO as external input and outputs additional alignments. Reliable alignments are gained through LMO as well as GMO according to the concept of reliability. The reliability is obtained by observing the linguistic comparability and structural comparability of the two ontologies being compared. We have performed Falcon-AO on tests provided by OAEI 2005 campaign and got some preliminary results. In this paper, we describe the architecture and techniques of Falcon-AO in brief and present our results in more details. Finally, comments abouttest cases and lessons learnt from the campaign will be presented.
Semantic Web,, Ontology Alignment,, Mapping,, Matching,, Similarity Measurement
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【期刊论文】WonderDesk-A Semantic Desktop for Resource Sharing and Management
瞿裕忠, Xiang Zhang, Wennan Shen, Yuzhong Qu
,-0001,():
-1年11月30日
We present our approach in building WonderDesk-a semantic desktop for resource sharing and management, which is a component of our WonderSpace application and designed to be an e-Science tool. We propose a desktop architecture for resource sharing and management using semanticenriched RSS model and P-P technology. To enable fine-grained metadata for e-Science, an ontology about resource is presented as basic vocabulary to be used in constructing resource metadata along with RSS. Further, group-specific discipline ontology is proposed to enhance the semantic description of information resource within user group.
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【期刊论文】An RDF Storage and Query Framework with Flexible Inference Strategy
瞿裕忠, Wennan Shen and Yuzhong Qu
APWeb 2006, LNCS 3841, pp. 166-175, 2006.,-0001,():
-1年11月30日
In the Semantic Web, RDF (Resource Description Framework) and RDF Schema are commonly used to describe metadata. There are a great many RDF data in current web, therefore, efficient storage and retrieval of large RDF data sets is required. So far, several RDF storage and query system are developed. According to the inference strategy they used, they can be classified into two categories, one exclusively use forward chaining strategy; the other exclusively use backward chaining strategy. In most cases, the query performance of the former is superior to that of the latter. However, in some cases, the disadvantage of larger storage space may at some point outweigh the advantage of faster querying. Further, the existing systems that exclusively use forward chaining strategy have not yet presented a good solution to the deletion operation by now. In this paper, we design a RDF storage and query framework with flexible inference strategy, which can combine forward and backward chaining inference strategies. In addition, a new solution to the deletion operation is also given within our framework. The feasibility of our framework is illustrated by primary experiments.
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