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 have been developing Robotic Communication Terminals (RCT) which support the self-mobility of the elderly and disabled people. One of the terminals we developed is "user-carried mobile terminal" which giv...
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We have been developing Robotic Communication Terminals (RCT) which support the self-mobility of the elderly and disabled people. One of the terminals we developed is "user-carried mobile terminal" which gives the information such as the navigation to visually and hearing impaired people who can walk by themselves. In this paper, we introduce the animation system to show the sign language for hearing impaired people and the voice guidance system for visually impaired people with the infrared communication and AM radio communication.
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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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.
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.
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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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.
The WATERS Network (WATer and Environmental Research Systems Network) will be an integrated real-time distributed observing system which will enable academic and government scientists, engineers, educators, and practi...
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This paper addresses the issue of ontology caching on semantic web. The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work ...
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ISBN:
(纸本)3540311424
This paper addresses the issue of ontology caching on semantic web. The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation. Ontology serves as the metadata for defining the information on semantic web. Ontology based semantic information retrieval (semantic retrieval) is becoming more and more important. Many research and industrial works have been made so far on semantic retrieval. Ontology based retrieval improves the performance of search engine and web mining. In semantic retrieval, a great number of accesses to ontologies usually lead the ontology servers to be very low efficient. To address this problem, it is indeed necessary to cache concepts and instances when ontology server is running. Existing caching methods from database community can be used in the ontology cache. However, they are not sufficient for dealing with the problem. In the task of caching in database, usually the most frequently accessed data are cached and the recently less frequently accessed data in the cache are removed from it. Different from that, in ontology base, data are organized as objects and relations between objects. User may request one object, and then request another object according to a relation of that object. He may also possibly request a similar object that has not any relations to the object. Ontology caching should consider more factors and is more difficult. In this paper, ontology caching is formalized as a problem of classification. In this way, ontology caching becomes independent from any specific semantic web application. An approach is proposed by using machine learning methods. When an object (e.g. concept or instance) is requested, we view its similar objects as candidates. A classification model is then used to predict whether each of these candidates should be cached or not. Features in classification models are defined. Experimental results indicat
Service discovery protocols are extremely important for developing distributed applications in ad-hoc environments. However to perform Service Discovery in mobile ad-hoc networks requires the design and development of...
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