BibSonomy is a web-based social resource sharing system which allows users to organise and share bookmarks and publications in a collaborative manner. Apart from standard folksonomy features such as an intuitive user ...
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BibSonomy is a web-based social resource sharing system which allows users to organise and share bookmarks and publications in a collaborative manner. Apart from standard folksonomy features such as an intuitive user interface, navigation along all dimensions, or browser integration via RSS feeds, BibSonomy provides tag hierarchies, group management and privacy features, and numerous import and export functions.
We study the problem of answering queries given a set of mappings between peer ontologies. In addition to the schema mapping between peer ontologies, there are axioms to give constraints to classes and properties. We ...
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We study the problem of answering queries given a set of mappings between peer ontologies. In addition to the schema mapping between peer ontologies, there are axioms to give constraints to classes and properties. We propose a set of rules to build graphs for the axioms. Because the axioms have different properties, the generated graphs are classified into four sets. In each peer, its RDF/OWL query languages can support regular expressions. If it wants to be transitive along semantic paths in peer knowledge management systems, we must rewrite conjunctive and disjunctive queries between peers. Because conjunctive queries are well-understood, we focus on a novel algorithm to rewrite disjunctive queries along semantic paths based on the graphs. For all atoms of a disjunctive query, we consider its union as a set and find the maximum rewritings over peers through a graphical way. Finally we do extensive simulation experiments. The simulation results show our algorithm can generate more rewritings than the naive rewriting algorithm at each distance.
A new interconnection network for multi-core processor, named the triplet-based hierarchical interconnection network (THIN), is presented. The topology of the network is very-simple and it has obvious hierarchical, sy...
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A new interconnection network for multi-core processor, named the triplet-based hierarchical interconnection network (THIN), is presented. The topology of the network is very-simple and it has obvious hierarchical, symmetric and scalable characteristics. The compare results show THIN is superior to 2-D mesh to construct interconnection network when there are not too many nodes. Results of simulation showed that THIN is a promising choice for multi-core processor with low network latency and high throughput.
Association rule mining is one of the most important and basic technique in data mining, which has been studied extensively and has a wide range of applications. However, as traditional data mining algorithms usually ...
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Association rule mining is one of the most important and basic technique in data mining, which has been studied extensively and has a wide range of applications. However, as traditional data mining algorithms usually only focus on analyzing data organized in single table, applying these algorithms in multi-relational data environment will result in many problems. This paper summarizes these problems, proposes a framework for the mining of multi-relational association rule, and gives a definition of the mining task. After classifying the existing work into two categories, it describes the main techniques used in several typical algorithms, and it also makes comparison and analysis among them. Finally, it points out some issues unsolved and some future further research work in this area.
Social resource sharing systems like YouTube and *** have acquired a large number of users within the last few years. They provide rich resources for data analysis, information retrieval, and knowledge discovery appli...
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Recent advances in database related applications propose many new challenges and have inspired database researchers and practitioners to further make their efforts on new database technologies.
Recent advances in database related applications propose many new challenges and have inspired database researchers and practitioners to further make their efforts on new database technologies.
The classical algorithm of finding association rules generated by a frequent itemset has to generate all non-empty subsets of the frequent itemset as candidate set of consequents. Xiongfei Li aimed at this and propose...
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The classical algorithm of finding association rules generated by a frequent itemset has to generate all non-empty subsets of the frequent itemset as candidate set of consequents. Xiongfei Li aimed at this and proposed an improved algorithm. The algorithm finds all consequents layer by layer, so it is breadth-first. In this paper, we propose a new algorithm Generate Rules by using Set-Enumeration Tree (GRSET) which uses the structure of Set-Enumeration Tree and depth-first method to find all consequents of the association rules one by one and get all association rules correspond to the consequents. Experiments show GRSET algorithm to be practicable and efficient.
Because mining complete set of frequent patterns from dense database could be impractical, an interesting alternative has been proposed recently. Instead of mining the complete set of frequent patterns, the new model ...
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Because mining complete set of frequent patterns from dense database could be impractical, an interesting alternative has been proposed recently. Instead of mining the complete set of frequent patterns, the new model only finds out the maximal frequent patterns, which can generate all frequent patterns. FP-growth algorithm is one of the most efficient frequent-pattern mining methods published so far. However, because FP-tree and conditional FP-trees must be two-way traversable, a great deal memory is needed in process of mining. This paper proposes an efficient algorithm Unid_FP-Max for mining maximal frequent patterns based on unidirectional FP-tree. Because of generation method of unidirectional FP-tree and conditional unidirectional FP-trees, the algorithm reduces the space consumption to the fullest extent. With the development of two techniques: single path pruning and header table pruning which can cut down many conditional unidirectional FP-trees generated recursively in mining process, Unid_FP-Max further lowers the expense of time and space.
As context-aware systems become more widespread and mobile there is an increasing need for a common distributed event platform for gathering context information and delivering to context-aware applications. The likely...
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Since we can hardly get semantics from the low-level features of the image, it is much more difficult to analyze the image than textual information on the Web. Traditionally, textual information around the image is us...
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