Junping Sun - Academia.edu (original) (raw)

Papers by Junping Sun

Research paper thumbnail of Heuristic and Hybrid Methods for Finding Global Minimum of Error Function in Artificial Neural Networks

Research paper thumbnail of Multidimensional Data Partitioning for Parallel Data Processing in Large Data Warehouses

Research paper thumbnail of On Semantic Evaluation of Preference Queries

International MultiConference of Engineers and Computer Scientists, 2006

Research paper thumbnail of Mining attribute association in query predicates for access path generation

This paper presents a framework to mine query predicates from query patterns in order to produce ... more This paper presents a framework to mine query predicates from query patterns in order to produce candidate attributes from query predicates for index generation and access path selection. Query predicates are query conditions or constraints involving tables to be accessed and values of attributes or columns to be retrieved in the format of the tuples or objects. Access path and its auxiliary data structures determine how data tuples and objects to be retrieved efficiently, in turn, the performance of data query processing. This framework mines set of query patterns, analyzes the association of attributes, and provides heuristics for access path generation and selection.

Research paper thumbnail of Multidimensional Range Data Partitioning for Parallel Data Processing

Research paper thumbnail of Data Management and Data Mining

Preface It is our great pleasure to announce the publication of the special issue of JCST, "... more Preface It is our great pleasure to announce the publication of the special issue of JCST, " Advances in Computer Science and Technology (Part 2) — Current Advances in the Research of the NSFC Joint Research Fund for Overseas Chinese Scholars and Scholars in Hong Kong and Macao ". Although some background information was introduced in Part 1 of the special issue published in July 2014, we would like to introduce again here for self-containing. First, as indicated by the issue name, it presents several achievements in the coordinative research between scholars in mainland China and young overseas Chinese scholars as well as young Chinese scholars in Hong Kong and Macao supported by the National Natural Science Foundation of China (NSFC). In the year of 1999, NSFC set up two programs " Joint Research Fund for Overseas Chinese Young Scholars " and " Joint Research Fund for Hong Kong and Macao Young Scholars " for overseas Chinese scholars and scholars in Hong Kong and Macao to support their high-level joint research with researchers in mainland China. And then these two programs were combined into one program " NSFC Joint Research Fund for Overseas Chinese Scholars and Scholars in Hong Kong and Macao " in the year of 2008. Different from some other NSFC programs, the recipients of the projects in this program need to be young and outstanding in their research fields. Thus this fund is not only a financial support, but also a kind of recognition or award. This requirement provides a solid basis for outstanding achievements in their research. Second, the topics of the papers published in this special issue are not limited to a specific research field. They cover a quite broad spectrum in computer science and technology. The third is that, not only are particular scientific or technological research results included in this issue, but also review papers of recent advances and hot topics and important research directions are included. Thus, the issue is special, but also it is general at the same time. Algorithms for the Pattern Matching with Flexible Wildcards (PMFW) problem are significant for the applications in bioinformatics, text search, information security, etc. The paper by Wu et al. gives a survey of the algorithm design for the PMFW problem. Challenges and opportunities in the research field are also presented. Gradating mispronunciations is an important technique for computer-aided pronunciation training. The paper by …

Research paper thumbnail of Cardinality-Based Quantitative Rule Derivation

Research paper thumbnail of Session details: Database theory, technology, and applications

Research paper thumbnail of Session details: Artificial intelligence & agents, information systems, and software development: Database theory, technology, and applications track

Research paper thumbnail of Alpha Cut Based Rule Derivation from Uncertain Data

Information-an International Interdisciplinary Journal, 2001

Research paper thumbnail of Database Systems Revisited: Concepts, Issues, and Trends

Research paper thumbnail of Multidimensional Histogram for Dynamic Data Exploration and Mining

Research paper thumbnail of Temporal Join with Hilbert Curve Mapping and Adaptive Buffer Management

International journal of software innovation, Apr 1, 2014

Research paper thumbnail of Session details: DTTA - database theory, technology and applications track

Proceedings of the Symposium on Applied Computing, 2017

The world nowadays revolves around dealing with extreme large amount of data presented in various... more The world nowadays revolves around dealing with extreme large amount of data presented in various formats. So it is inevitable that researchers focus on advancing the state of managing information. From here, the importance of database technology ranks amongst the hottest areas of research, taking into account the consistent need for faster query processing as well as for managing huge amounts of data. This year the track has received many papers covering different areas of databases.

Research paper thumbnail of Optimization of Paging Cost in Mobile Switching System by Genetic Algorithm

Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, 2020

Research paper thumbnail of Past, Current and Future of Deductive Query Processing

Research paper thumbnail of Incremental Rule Derivation via Multidimensional Data Partitioning

Research paper thumbnail of Knowledge discovery by attribute-oriented approach under directed acyclic concept graph (dacg)

Knowledge discovery in databases (KDD) is an active and promising research area with potentially ... more Knowledge discovery in databases (KDD) is an active and promising research area with potentially high payoffs in business and scientific applications. The great challenge of knowledge discovery in databases is to process large quantities of raw data automatically, to identify the most significant and meaningful patterns, and to present this knowledge in an appropriate form for decision making and other purposes. In previous researches, Attribute-Oriented Induction, implemented artificial intelligence, “learning from examples” paradigm. This method integrates traditional database operations to extract rules from database systems. The key techniques in attribute-oriented induction are attribute generalization and undesirable attribute removal. Attribute generalization is implemented by replacing a low-level concept with its corresponding high level concept. The core part of this approach is a concept hierarchy, which is a linear tree schema built on each individual and independent dom...

Research paper thumbnail of Session details: Information systems: DTTA - database theory, technology, and applications track

Proceedings of the 33rd Annual ACM Symposium on Applied Computing, 2018

Research paper thumbnail of Directed acyclic concept graph based attribute oriented induction

2001 IEEE International Conference on Systems, Man and Cybernetics. e-Systems and e-Man for Cybernetics in Cyberspace (Cat.No.01CH37236)

This paper introduces an attribute oriented induction method on a directed acyclic concept graph ... more This paper introduces an attribute oriented induction method on a directed acyclic concept graph to perform the task of knowledge discovery on a given relational database (table) for rule derivation. Our proposed method is different from previous approaches such as basic attribute oriented induction, rule-based attribute oriented induction, and path-id based attribute oriented induction in avoiding backtracking and information loss

Research paper thumbnail of Heuristic and Hybrid Methods for Finding Global Minimum of Error Function in Artificial Neural Networks

Research paper thumbnail of Multidimensional Data Partitioning for Parallel Data Processing in Large Data Warehouses

Research paper thumbnail of On Semantic Evaluation of Preference Queries

International MultiConference of Engineers and Computer Scientists, 2006

Research paper thumbnail of Mining attribute association in query predicates for access path generation

This paper presents a framework to mine query predicates from query patterns in order to produce ... more This paper presents a framework to mine query predicates from query patterns in order to produce candidate attributes from query predicates for index generation and access path selection. Query predicates are query conditions or constraints involving tables to be accessed and values of attributes or columns to be retrieved in the format of the tuples or objects. Access path and its auxiliary data structures determine how data tuples and objects to be retrieved efficiently, in turn, the performance of data query processing. This framework mines set of query patterns, analyzes the association of attributes, and provides heuristics for access path generation and selection.

Research paper thumbnail of Multidimensional Range Data Partitioning for Parallel Data Processing

Research paper thumbnail of Data Management and Data Mining

Preface It is our great pleasure to announce the publication of the special issue of JCST, "... more Preface It is our great pleasure to announce the publication of the special issue of JCST, " Advances in Computer Science and Technology (Part 2) — Current Advances in the Research of the NSFC Joint Research Fund for Overseas Chinese Scholars and Scholars in Hong Kong and Macao ". Although some background information was introduced in Part 1 of the special issue published in July 2014, we would like to introduce again here for self-containing. First, as indicated by the issue name, it presents several achievements in the coordinative research between scholars in mainland China and young overseas Chinese scholars as well as young Chinese scholars in Hong Kong and Macao supported by the National Natural Science Foundation of China (NSFC). In the year of 1999, NSFC set up two programs " Joint Research Fund for Overseas Chinese Young Scholars " and " Joint Research Fund for Hong Kong and Macao Young Scholars " for overseas Chinese scholars and scholars in Hong Kong and Macao to support their high-level joint research with researchers in mainland China. And then these two programs were combined into one program " NSFC Joint Research Fund for Overseas Chinese Scholars and Scholars in Hong Kong and Macao " in the year of 2008. Different from some other NSFC programs, the recipients of the projects in this program need to be young and outstanding in their research fields. Thus this fund is not only a financial support, but also a kind of recognition or award. This requirement provides a solid basis for outstanding achievements in their research. Second, the topics of the papers published in this special issue are not limited to a specific research field. They cover a quite broad spectrum in computer science and technology. The third is that, not only are particular scientific or technological research results included in this issue, but also review papers of recent advances and hot topics and important research directions are included. Thus, the issue is special, but also it is general at the same time. Algorithms for the Pattern Matching with Flexible Wildcards (PMFW) problem are significant for the applications in bioinformatics, text search, information security, etc. The paper by Wu et al. gives a survey of the algorithm design for the PMFW problem. Challenges and opportunities in the research field are also presented. Gradating mispronunciations is an important technique for computer-aided pronunciation training. The paper by …

Research paper thumbnail of Cardinality-Based Quantitative Rule Derivation

Research paper thumbnail of Session details: Database theory, technology, and applications

Research paper thumbnail of Session details: Artificial intelligence & agents, information systems, and software development: Database theory, technology, and applications track

Research paper thumbnail of Alpha Cut Based Rule Derivation from Uncertain Data

Information-an International Interdisciplinary Journal, 2001

Research paper thumbnail of Database Systems Revisited: Concepts, Issues, and Trends

Research paper thumbnail of Multidimensional Histogram for Dynamic Data Exploration and Mining

Research paper thumbnail of Temporal Join with Hilbert Curve Mapping and Adaptive Buffer Management

International journal of software innovation, Apr 1, 2014

Research paper thumbnail of Session details: DTTA - database theory, technology and applications track

Proceedings of the Symposium on Applied Computing, 2017

The world nowadays revolves around dealing with extreme large amount of data presented in various... more The world nowadays revolves around dealing with extreme large amount of data presented in various formats. So it is inevitable that researchers focus on advancing the state of managing information. From here, the importance of database technology ranks amongst the hottest areas of research, taking into account the consistent need for faster query processing as well as for managing huge amounts of data. This year the track has received many papers covering different areas of databases.

Research paper thumbnail of Optimization of Paging Cost in Mobile Switching System by Genetic Algorithm

Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, 2020

Research paper thumbnail of Past, Current and Future of Deductive Query Processing

Research paper thumbnail of Incremental Rule Derivation via Multidimensional Data Partitioning

Research paper thumbnail of Knowledge discovery by attribute-oriented approach under directed acyclic concept graph (dacg)

Knowledge discovery in databases (KDD) is an active and promising research area with potentially ... more Knowledge discovery in databases (KDD) is an active and promising research area with potentially high payoffs in business and scientific applications. The great challenge of knowledge discovery in databases is to process large quantities of raw data automatically, to identify the most significant and meaningful patterns, and to present this knowledge in an appropriate form for decision making and other purposes. In previous researches, Attribute-Oriented Induction, implemented artificial intelligence, “learning from examples” paradigm. This method integrates traditional database operations to extract rules from database systems. The key techniques in attribute-oriented induction are attribute generalization and undesirable attribute removal. Attribute generalization is implemented by replacing a low-level concept with its corresponding high level concept. The core part of this approach is a concept hierarchy, which is a linear tree schema built on each individual and independent dom...

Research paper thumbnail of Session details: Information systems: DTTA - database theory, technology, and applications track

Proceedings of the 33rd Annual ACM Symposium on Applied Computing, 2018

Research paper thumbnail of Directed acyclic concept graph based attribute oriented induction

2001 IEEE International Conference on Systems, Man and Cybernetics. e-Systems and e-Man for Cybernetics in Cyberspace (Cat.No.01CH37236)

This paper introduces an attribute oriented induction method on a directed acyclic concept graph ... more This paper introduces an attribute oriented induction method on a directed acyclic concept graph to perform the task of knowledge discovery on a given relational database (table) for rule derivation. Our proposed method is different from previous approaches such as basic attribute oriented induction, rule-based attribute oriented induction, and path-id based attribute oriented induction in avoiding backtracking and information loss