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International Conference on Semantics, knowledge and Grid (SKG)

作者： Xuan Tian Haihua Li Xiaoyong Du School of Information Renmin University of China Beijing China Key Laboratory of Data Engineering and Knowledge Engineering MOESchool of Information Renmin University of China Beijing China

In domain ontology, semantic association (SA) is used to depict the correlation between two concepts. In this paper, we define semantic association degree (SAD) for measuring SA in the domain ontology. We first present a method to measure SAD of two direct related concepts by evaluating the semantic relationship between them, and then give another method to measure SAD of two indirect related concepts though SAD of two directed neighboring concepts. A set of comparison experiments show the benefit of our approaches.

关键词： Ontologies Psychology data mining Diseases Information retrieval Laboratories data engineering knowledge engineering Text categorization History

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Finding Top-k Min-Cost Connected Trees in databases

Finding Top-k Min-Cost Connected Trees in Databases

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International Conference on data engineering

作者： Bolin Ding Jeffrey Xu Yu Shan Wang Lu Qin Xiao Zhang Xuemin Lin Chinese University of Hong Kong China Key Laboratory of Data Engineering and Knowledge Engineering MOE of China Renmin University of China China University of New South Wales Australia

ISBN: (纸本)1424408024

It is widely realized that the integration of database and information retrieval techniques will provide users with a wide range of high quality services. In this paper, we study processing an l-keyword query, p 1 , p 1 , ..., p l , against a relational database which can be modeled as a weighted graph, G(V, E). Here V is a set of nodes (tuples) and E is a set of edges representing foreign key references between tuples. Let V i ⊆ V be a set of nodes that contain the keyword p i . We study finding top-k minimum cost connected trees that contain at least one node in every subset V i , and denote our problem as GST-k When k = 1, it is known as a minimum cost group Steiner tree problem which is NP-complete. We observe that the number of keywords, l, is small, and propose a novel parameterized solution, with l as a parameter, to find the optimal GST-1, in time complexity O(3 l n + 2 l ((l + logn)n + m)), where n and m are the numbers of nodes and edges in graph G. Our solution can handle graphs with a large number of nodes. Our GST-1 solution can be easily extended to support GST-k, which outperforms the existing GST-k solutions over both weighted undirected/directed graphs. We conducted extensive experimental studies, and report our finding.

关键词： Tree graphs Relational databases Costs Laboratories data engineering knowledge engineering Australia Information retrieval

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Milling of multi-relational association rules

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Ruan Jian Xue Bao/Journal of Software 2007年第11期18卷 2752-2765页

作者： He, Jun Liu, Hong-Yan Du, Xiao-Yong Department of Computer Science and Technology Renmin University of China Beijing 100872 China Department of Management Science and Engineering Tsinghua University Beijing 100084 China Key Laboratory of Data Engineering and Knowledge Engineering Beijing 100872 China

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.

关键词： data mining

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2DCMA： An Effective Maintenance Algorithm of Materialized Views in Peer data Management Systems

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Journal of Computer Science & Technology 2006年第4期21卷 503-512页

作者：覃飙王珊杜小勇 School of Information Renmin University of China Beijing 100872 P.R. China Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education Beijing 100872 P.R. China

Update management is very important for data integration systems. So update management in peer data management systems （PDMSs） is a hot research area. This paper researches on view maintenance in PDMSs. First, the definition of view is extended and the peer view, local view and global view are proposed according to the requirements of applications. There are two main factors to influence materialized views in PDMSs. One is that schema mappings between peers are changed, and the other is that peers update their data. Based on the requirements, this paper proposes an algorithm called 2DCMA, which includes two sub-algorithms： data and definition consistency maintenance algorithm% to effectively maintain views. For data consistency maintenance, Mork＇s rules are extended for governing the use of updategrams and boosters. The new rule system can be used to optimize the execution plan. And are extended for the data consistency maintenance algorithm is based on the new rule system. Furthermore, an ECA rule is adopted for definition consistency maintenance. Finally, extensive simulation experiments are conducted in SPDMS. The simulation results show that the 2DCMA algorithm has better performance than that of Mork＇s when maintaining data consistency. And the 2DCMA algorithm has better performance than that of centralized view maintenance algorithm when maintaining definition consistency.

关键词： view maintenance peer data management system schema mapping ECA rule

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Maintaining materialized relations incrementally to improve performance of ontology query

Maintaining materialized relations incrementally to improve ...

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7th International Conference on Web-Age Information Management Workshops, WAIM 2006

作者： Li, Man Du, Xiaoyong Wang, Shan School of Information Renmin University of China China Key Laboratory of Data Engineering and Knowledge Engineering MOE 100872 Beijing China

ISBN: (纸本)0769527051

For ontology-based applications, the efficiency of ontology query is vital. Different from existing approaches, the paper improves performance of ontology query by materializing some derived relations. Experimental results show that the integrated performance of ontology query can be improved greatly by maintaining materialized relations and the materialized relations technique has good scalability. Here the challenge is how to maintain the materialized relations incrementally with the update of ontologies. Because transitive relations are in common use in ontology, the paper proposes a novel algorithm for maintaining transitive materialized relations incrementally based on a special weighted materialized relation transitive graph, which can solve the coexistence problem of multiple derived paths better and proves the correctness of the algorithm. © 2006 IEEE.

关键词： Ontology

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NUITS: A Novel User Interface for Efficient keyword Search over databases

NUITS: A Novel User Interface for Efficient Keyword Search o...

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32nd International Conference on Very Large data Bases, VLDB 2006

作者： Wang, Shan Peng, Zhaohui Zhang, Jun Qin, Lu Wang, Sheng Yu, Jeffrey Xu Ding, Bolin School of Information Renmin Univ. of China Key Laboratory of Data Engineering and Knowledge Engineering MOE of China Beijing China Department of Systems Engineering and Engineering Management The Chinese Univ. of Hong Kong Hong Kong Hong Kong

ISBN: (纸本)1595933859

The integration of database and information retrieval techniques provides users with a wide range of high quality services. We present a prototype system, called NUITS, for efficiently processing keyword queries on top of a relational database. Our NUITS allows users to issue simple keyword queries as well as advanced keyword queries with conditions. The efficiency of keyword query processing and the user-friendly result display will also be addressed in this paper. Copyright 2006 VLDB Endowment, ACM

关键词： Query processing

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An Economic Semantic Web Platform

An Economic Semantic Web Platform

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International Conference on Grid and Cooperative Computing Workshops (GCCW)

作者： Xiaoyong Du He Hu Man Li Wenjuan Wu Guo Qin Key Laboratory of Data Engineering and Knowledge Engineering MOE School of Information Renmin University of China Beijing China

The paper describes an ongoing project which implements a subject-oriented semantic Web platform at Renmin Univ. of China. The economic semantic Web platform (ESWP) contains three components: collaborative ontology developing environment and repository system (CODERS); economic ontology annotation Web services (ConAnnotator); economic ontology and annotated resources. We describe each of these components in detail and illustrate some use cases of the ESWP

关键词： Semantic Web Ontologies Environmental economics Web services Collaboration Humans Software agents Application software Helium Laboratories

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NUITS: a novel user interface for efficient keyword search over databases 06

NUITS: a novel user interface for efficient keyword search o...

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Proceedings of the 32nd international conference on Very large data bases

作者： Shan Wang Zhaohui Peng Jun Zhang Lu Qin Sheng Wang Jeffrey Xu Yu Bolin Ding School of Information Renmin Univ. of China Key Laboratory of Data Engineering and Knowledge Engineering MOE of China Beijing China Department of Systems Engineering and Engineering Management The Chinese Univ. of Hong Kong Hong Kong China

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Survey on ontology learning research

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Ruan Jian Xue Bao/Journal of Software 2006年第9期17卷 1837-1847页

作者： Du, Xiao-Yong Li, Man Wang, Shan School of Information Renmin University of China Beijing 100872 China Key Laboratory of Data Engineering and Knowledge Engineering Beijing 100872 China

Recently, ontology learning is emerging as a new hotspot of research in computer science. In this paper the issue of ontology learning is divided into nine sub-issues according to the structured degree (structured, semi-structured, non-structured) of source data and learning objects (concept, relation, axiom) of ontology. The characteristics, major approaches and the latest research progress of the nine sub-issues are summarized. Based on the analysis framework proposed in the paper, existing ontology learning tools are introduced and compared. The problems of current research are discussed, and finally the future directions are pointed out.

关键词： Computer science

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Probabilistic Graph Pattern Matching via Tumor knowledge Graph

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ACM Transactions on Probabilistic Machine Learning 1000年

作者： Lei Li Houdie Tu Zhenchao Tao Chenyang Bu Xindong Wu Key Laboratory of Knowledge Engineering with Big Data (the Ministry of Education of China) Hefei University of Technology Hefei 230601 China and School of Computer Science and Information Engineering Hefei University of Technology Hefei 230601 China School of Computer Science and Information Engineering Hefei University of Technology Hefei 230601 China School of Data Science University of Science and Technology of China Hefei 230052 China and West District of the First Affiliated Hospital of University of Science and Technology of China Hefei 230031 China Key Laboratory of Knowledge Engineering with Big Data (the Ministry of Education of China) Hefei University of Technology Hefei 230601 China

Graph Pattern Matching (GPM) entails the identification of subgraphs within a larger graph structure that either precisely mirror or closely parallel a predefined pattern graph. Despite the fact that research on GPM in large-scale graph data has been largely centered on social network analysis or enhancing the precision and efficiency of matching algorithms for expeditious subgraph retrieval, there is a noticeable absence of studies committed to probing GPM in medical domains. To rectify this shortcoming and probe the potential of GPM in clinical contexts, particularly in aiding patients with the selection of optimal tumor treatment plans, this paper introduces the concept of probabilistic graph pattern matching specifically modified for the Tumor knowledge Graph (TKG). We propose a multi-constraint graph pattern matching algorithm, hereinafter designated as TKG-McGPM, customized for the Tumor knowledge Graph. Through experimental verification, we establish that TKG-McGPM can facilitate more efficient and informed decision-making in tumor treatment planning.

关键词： Graph Pattern Matching Probabilistic Graph Pattern Matching Tumor knowledge Graph Monte Carlo Method

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