ArchIS: an XML-based approach to transaction-time temporal database systems

Effective support for temporal applications by database systems represents an important technical objective that is difficult to achieve since it requires an integrated solution for several problems, including (i) expressive temporal representations and data models, (ii) powerful languages for temporal queries and snapshot queries, (iii) indexing, clustering and query optimization techniques for managing temporal information efficiently, and (iv) architectures that bring together the different pieces of enabling technology into a robust system. In this paper, we present the ArchIS system that achieves these objectives by supporting a temporally grouped data model on top of RDBMS. ArchIS’ architecture uses (a) XML to support temporally grouped (virtual) representations of the database history, (b) XQuery to express powerful temporal queries on such views, (c) temporal clustering and indexing techniques for managing the actual historical data in a relational database, and (d) SQL/XML for executing the queries on the XML views as equivalent queries on the relational database. The performance studies presented in the paper show that ArchIS is quite effective at storing and retrieving under complex query conditions the transaction-time history of relational databases, and can also assure excellent storage efficiency by providing compression as an option. This approach achieves full-functionality transaction-time databases without requiring temporal extensions in XML or database standards, and provides critical support to emerging application areas such as RFID.     

Using UML to model relational database operations

The Unified Modeling Language (UML) is being used as the de-facto standard in the software industry. With the adoption of UML 2.0, the new enhancements allow this version to describe many of the elements found in today's software technology as well as Model Driven Architecture and Service-Oriented Architecture. Although the Object Management Group (OMG) has released several UML Profiles to tailor the language to specific areas, relational database modeling is not fully addressed in these profiles. Many existing software applications involve complex application layer implemented in object-oriented programming languages and at the same time use relational database systems as the back-end data store. Modeling the whole system in a consistent manner will help developers and end users better understand the application. In this work we show how to model relational database operations using UML. Atomic database operations are modeled based on our framework and are used as building blocks to model more complex database operations.     

基于本体的异构数据库集成方法

随着数据库种类的增多,在查询不同数据库时,经常碰到用户术语和数据库术语不匹配的问题.提出了一种基于本体理论的异构数据库集成方法,该方法利用了一个全局字典,建立各局部数据库的本体,通过中间件和局部查询代理处理用户请求,用他们自己的术语(不精确查询)进行查询.给出了本体模型和查询处理算法以及原型系统的实现.     

A functional approach to database updates

PFL is a functional database language in which functions are defined equationally and bulk data is stored using a special class of functions called selectors. It is a lazy language, supports higher-order functions, has a strong polymorphic type inference system, and allows new user-defined data types and values to be declared. All functions, types and values persist in a database. Functions can be written which update all aspects of the database: by adding data to selectors, by defining new equations, and by introducing new data types and values. PFL is “semi-referentially transparent”, in the sense that whilst updates are referentially opaque and are executed destructively, all evaluation is referentially transparent. Similarly, type checking is “semi-static” in the sense that whilst updates are dynamically type checked at run time, expressions are type checked before they are evaluated and no type errors can occur during their evaluation.

In this paper we examine the expressiveness of PFL with respect to updates, and illustrate the language by developing a number of general purpose update functions, including functions for restructuring selectors, for memoisation, and for generating unique system identifiers. We also provide a translation mechanism between Datalog programs and equations, and show how different Datalog evaluation strategies can be supported.     

Cluster approach to the domains formation

As a rule, the quadratic functional depending on a great number of binary variables has a lot of local minima. One of approaches allowing to find (in averaged) deeper local minima is aggregation of binary variables into larger blocks/domains. To minimize the functional one has to change the states of aggregated variables (domains). In present publication we discuss methods of domains formation. It is shown that the best results are obtained when domains are formed by variables that are strongly connected with each other.     

A deontic approach to database integrity

The logical theory of database integrity is developed as an application of deontic logic. After a brief introduction to database theory and Kripke semantics, a deontic operator X, denoting what should hold, non-trivially, given a set of constraints, is defined and axiomatized. The theory is applied to updates, to dynamic constraints and to databases extended with nulls.     

A hybrid evolutionary approach for solving constrained optimization problems over finite domains

A novel approach for the integration of evolution programs and constraint-solving techniques over finite domains is presented. This integration provides a problem-independent optimization strategy for large-scale constrained optimization problems over finite domains. In this approach, genetic operators are based on an arc-consistency algorithm, and chromosomes are arc-consistent portions of the search space of the problem. The paper describes the main issues arising in this integration: chromosome representation and evaluation, selection and replacement strategies, and the design of genetic operators. We also present a parallel execution model for a distributed memory architecture of the previous integration. We have adopted a global parallelization approach that preserves the properties, behavior, and fundamentals of the sequential algorithm. Linear speedup is achieved since genetic operators are coarse grained as they perform a search in a discrete space carrying out arc consistency. The implementation has been tested on a GRAY T3E multiprocessor using a complex constrained optimization problem.     

On a human-centred approach to database systems

It is often illuminating to view a technology or a methodology from a novel perspective, thereby assessing it with criteria which are likely to differ markedly from those used by its designers. In this paper we review current database design methodology and, implicitly, database technology. We attempt to show that both are founded on an information-centred philosophy, and that the consequences of this view are significant and unsatisfactory. We investigate an alternative, human-centred philosophy and relate this to the more limited scope of a user-centred view which evolves from our analysis.     

A model-driven approach to semi-structured database design

Recently XML has become a standard for data representation and the preferred method of encoding structured data for exchange over the Internet. Moreover it is frequently used as a logical format to store structured and semi-structured data in databases. We propose a model-driven and configurable approach for modeling hierarchical XML data using object role modeling (ORM) as a flat conceptual model. First a non-hierarchical conceptual schema of the problem domain is built using ORM and then different hierarchical views of the conceptual schema or parts of it are specified by the designer using transformation rules. A hierarchical modeling notation called H-ORM is proposed to show these hierarchical views and model more complex semi-structured data constructs and constraints. We also propose an algorithm to map hierarchical H-ORM views to XML schema language.     

A data mining approach to database compression

Data mining can dig out valuable information from databases to assist a business in approaching knowledge discovery and improving business intelligence. Database stores large structured data. The amount of data increases due to the advanced database technology and extensive use of information systems. Despite the price drop of storage devices, it is still important to develop efficient techniques for database compression. This paper develops a database compression method by eliminating redundant data, which often exist in transaction database. The proposed approach uses a data mining structure to extract association rules from a database. Redundant data will then be replaced by means of compression rules. A heuristic method is designed to resolve the conflicts of the compression rules. To prove its efficiency and effectiveness, the proposed approach is compared with two other database compression methods. Chin-Feng Lee is an associate professor with the Department of Information Management at Chaoyang University of Technology, Taiwan, R.O.C. She received her M.S. and Ph.D. degrees in 1994 and 1998, respectively, from the Department of Computer Science and Information Engineering at National Chung Cheng University. Her current research interests include database design, image processing and data mining techniques. S. Wesley Changchien is a professor with the Institute of Electronic Commerce at National Chung-Hsing University, Taiwan, R.O.C. He received a BS degree in Mechanical Engineering (1989) and completed his MS (1993) and Ph.D. (1996) degrees in Industrial Engineering at State University of New York at Buffalo, USA. His current research interests include electronic commerce, internet/database marketing, knowledge management, data mining, and decision support systems. Jau-Ji Shen received his Ph.D. degree in Information Engineering and Computer Science from National Taiwan University at Taipei, Taiwan in 1988. From 1988 to 1994, he was the leader of the software group in Institute of Aeronautic, Chung-Sung Institute of Science and Technology. He is currently an associate professor of information management department in the National Chung Hsing University at Taichung. His research areas focus on the digital multimedia, database and information security. His current research areas focus on data engineering, database techniques and information security. Wei-Tse Wang received the B.A. (2001) and M.B.A (2003) degrees in Information Management at Chaoyang University of Technology, Taiwan, R.O.C. His research interests include data mining, XML, and database compression.     

IESK-ArDB: a database for handwritten Arabic and an optimized topological segmentation approach

Even though a lot of researches have been conducted in order to solve the problem of unconstrained handwriting recognition, an effective solution is still a serious challenge. In this article, we address two Arabic handwriting recognition-related issues. Firstly, we present IESK-arDB, a new multi-propose off-line Arabic handwritten database. It is publicly available and contains more than 4,000 word images, each equipped with binary version, thinned version as well as a ground truth information stored in separate XML file. Additionally, it contains around 6,000 character images segmented from the database. A letter frequency analysis showed that the database exhibits letter frequencies similar to that of large corpora of digital text, which proof the database usefulness. Secondly, we proposed a multi-phase segmentation approach that starts by detecting and resolving sub-word overlaps, then hypothesizing a large number of segmentation points that are later reduced by a set of heuristic rules. The proposed approach has been successfully tested on IESK-arDB. The results were very promising, indicating the efficiency of the suggested approach.     

基于规则的关系数据库到本体的转换方法

提出了一种新的全自动的关系数据库到本体的转换方法,通过分析关系模式的主键、属性、引用关系、完整性约束和部分数据来创建本体,尽量保持了关系数据库的信息,并在构建的过程中对信息进行初步的集成和分类.系统实践证明,该方法可自动进行关系模式和数据到本体的等价转换,而且完成了对关系数据库中部分语义信息的辅助挖掘.     

Physical database design: A DSS approach

This paper presents a working decision support system for use in the physical design of a database. Physical database design, a structured decision problem, lends itself to a decision support approach because closed form algorithms are computationally infeasible. The paper describes the physical database design problem, presents an overview of a software system for use in solving this problem, and evaluates the use of the system in solving a sample problem.     

Towards a new approach to secure database design

The problem of designing and managing a secure database system is considered in this paper. The approach which is proposed is primarily concerned with the security information definition and management in a database environment. A multiphase design methodology is presented reflecting current proposals of database design methodology. In particular four design phases are proposed: requirements analysis of the security system, conceptual, logical and physical design of security information. The content and the solution techniques of each phase are examined. A database management system architecture is also presented which is suitable to control access rights to the database.     

A New Approach to Database Auto-Design by Logic

The database auto-design is an important problem in database research.In this paper we propose some new ideas and an approach called “logic approach” to implement the database auto-design.Given a relational scheme and a set of the functional dependencies for the relation we can obtain all of the functional dependencies and key for the relation and determine the normal form the relation satisfies.