Text processing is an important computer application. Due to its importance, a number of text manipulation programming languages have been devised (e.g. Icon). These programming languages are very useful for applications such as natural language processing, text analysis, text editing, document formatting, text generation, etc. However, they were mainly designed to handle English texts, and are ineffective for Chinese. This is because English and Chinese texts are represented very differently in a computer. An English character is mainly represented in 7-bit ASCII, and its Chinese counterpart commonly in 16-bit GB or BIG-5. This difference makes direct application of English-based text manipulation programming languages to Chinese erroneous, e.g. application of Icon to reverse a string of Chinese characters. In this paper, a new dialect of Icon, referred to as Chicon (i.e. Chinese Icon), is proposed. In the design of Chicon, new data types were introduced to differentiate pure English and English/Chinese mixed texts. In addition, existing Icon text manipulation functions were modified to account for Chinese texts. Experiments have shown that Chicon not only could overcome the problems of Chinese processing in Icon, but its execution speed was actually superior to Icon in handling Chinese. Furthermore, application of Chicon to a real sized problem, namely word segmentation, has proved that the language is practical. © 1998 John Wiley & Sons, Ltd.

The increasing data size in Chinese information-based applications renders conventional information retrieval (IR) systems unsuitable. This is because they are limited in both storage and speed. To overcome these predicaments, a parallel Chinese IR system (CIR) has been designed. It is being developed on a SIMD parallel computer, DECmpp, which is configured with 8,192 processing elements. It uses full inverted indices for retrieval. The "divide-and-conquer" principle is exercised in exploiting data parallelism in the inverted index files. The inverted indices are first partitioned into fragments. Each fragment is then assigned to an individual processing elements. Thereafter, during an index retrieval operation, all index fragments are searched in parallel. Although the principle is simple, realising the parallel indexing algorithm in a naive fashion (i.e. without considering the underlying parallel architecture) would result in poor retrieval performance. During the design of the CIR system, 3 different implementation models for parallel indexing have been considered. In this paper, qualitative evaluation of the 3 models is presented. Based on the result of the evaluation, the model that offers the best run-time performance was adopted.>

A visual interface for a multimedia database management system (MDBMS) is described. DBMS query languages are linear in syntax. Although natural language interfaces have been found to be useful, natural language is ambiguous and difficult to process. For queries on standard (relational) data, these difficulties can be avoided with the use of a visual, graphical interface to guide the user in specifying the query. For image and other media data which are ambiguous in nature, natural language processing, combined with direct graphical access to the domain knowledge, is used to interpret and evaluate the natural language query. The system fully supports graphical and image input/output in different formats. The combination of visual effect and natural language specification, the support of media data, and the allowance of incremental query specification simplify the process of query specification not only for image or multimedia databases but also for all databases.>

A description is given of the DEMOM media object data model, which aims at providing a uniform framework for managing different types of media data i.e. images, text, sound or graphics. According to DEMOM, media objects are defined as a class hierarchy of objects, i.e., images, text, sound, and graphics are subtypes of the general type media object. Representation-specific objects are regarded as subordinate types of the corresponding subtype, e.g., a SUN raster image in pixrect format is an instance of the subtype pixrect which is in turn a subtype of image. Using images as an example the authors discuss the media object hierarchy, the corresponding access operations, and implementation issues. Content-oriented search of media data on the basis of predicate calculus is considered as an essential part of DEMOM and hence briefly outlined. Finally, concerns related to the integration of alphanumeric and media objects are also included.>

The domain of statistical and scientific databases is targeted here, and the class of aggregate queries which are very often encountered in this domain is considered. Such a query is aimed at retrieving some aggregate characteristics of the raw data. The tree-based statistics access method (TBSAM), which provides support for the efficient processing of aggregate queries, is presented. It is related to the B/sup +/-tree and also processes the B/sup +/-tree's efficient update properties. Complementing TBSAM is the provision of a grouped update algorithm for minimizing expensive indexed database updates.>

A novel database access method for statistical database processing is discussed. The structure of the access method and its application for the processing of statistical queries is shown. Descriptive statistics on attributes of the data can be calculated very efficiently. In addition, the structure is suited for queries involving order statistics on an index attribute. An extra advantage provided by the structure is the ability to do various kinds of sampling. The cost of processing various queries is analyzed. Structural updates to the access method are discussed.>

As advanced applications become more and more demanding, the use of the data on hand becomes more and more sophisticated. In applications such as the kind in commercial banking environment, the search for data is rather simple and precise; the time constraints are not severe; statistical applications are not often used; history data is not so important; and estimates are not performed. In short, the demand to have an intelligent DB is at best minimal.

Recently, extensions for relational database management systems (DBMS) have been proposed to support also hierarchical structures (complex objects). These extensions have been mainly implemented on top of an existing DBMS. Such an approach leads to many disadvantages not only from the conceptual point of view but also from performance aspects. Thus paper reports on a 3-year effort to design and prototype a DBMS to support a generalized relational data model, called extended NF2 (Non First Normal Form) data model which treats flat relations, lists, and hierarchical structures in a uniform way. The logical data model, a language for this model, and alternatives for storage structures to implement generalized relations are presented and discussed.

One of the most difficult tasks in database design is the collection of relevant information needed for database design. This information can be separated into two categories: information about the processes which use, modify or produce the data, and information about the data which is used, modified, or produced by the processes. This paper describes a "forms" oriented requirements specification facility as a formal means for capturing the information crucial for database design. Both kinds of information are expressible by the proposed structured forms specification. Furthermore, not only the application usage, but also the integrity constraints that must be maintained in the database can be captured in a concise, unambiguous and machine manipulable manner. The concepts underlying the forms approach are few and simple, hence it is easy to use for the database designer and can be understood by non-computer specialists. This facilitates the cooperation from users to participate in the specification of database application requirements.

Business activities, in general, involve data processing (such as queries, extraction, manipulation, and restructuring of data, etc.) as well as conventional office work centered around preparation, distribution, and filing and retrieval of documents. Convinced that most of these activities can be expressed in terms of forms, we present in this paper a formal means for specification of forms processing. The underlying concept is that business functions can be decomposed into meaningfuliy connected form processes where each process either produces or modifies a form. Powerful constructs are provided so that most of the common data processing activities can be expressed in a very high level, concise, and yet compilable manner.

EXPRESS is an experimental prototype data translation system which can access a wide variety of data and restructure it for new uses. The system is driven by two very high level nonprocedural languages: DEFINE for data description and CONVERT for data restructuring. Program generation and cooperating process techniques are used to achieve efficient operation. This paper describes the design and implementation of EXPRESS. DEFINE and CONVERT are summarized and the implementation architecture presented. The DEFINE description is compiled into a customized PL/1 program for accessing source data. The restructuring specified in CONVERT is compiled into a set of customized PL/1 procedures to derive multiple target files from multiple input files. Job steps and job control statements are generated automatically. During execution, the generated procedures run under control of a process supervisor, which coordinates buffer management and handles file allocation, deallocation, and all input/output requests. The architecture of EXPRESS allows efficiency in execution by avoiding unnecessary secondary storage references while at the same time allowing the individual procedures to be independent of each other. Its modular structure permits the system to be extended or transferred to another environment easily.

This paper describes in detail a translation definition language, CONVERT, for specifying the mapping of the instances of source items, which may be components of one or more files, into instances of target data, which may constitute multiple files.The language is designed for the class of users who are familiar with the logical aspects of their data, know what they want to be done, but do not want to be concerned with the details of how to accomplish it. It is high level and non-procedural according to current standards.The language provides very powerful and highly flexible restructuring capability. Although primarily designed for hierarchically structured data, it is applicable to other kinds of data structures as well. It is believed that the language can handle all common processes required in a data translation. Furthermore, the simple underlying concepts enable the users to visualize the translation processes, thus making data conversion a much simpler task. Examples to illustrate the languages' applications are included.

The design of a file system has never been a simple nor a straightforward task because of its complexity. Heuristics and experience still play a major role in guiding the design process. To organize the entire design process in a more systematic manner, large scale simulation has proved to be an effective technique. The FOREM models developed during the past several years (specifically for the evaluation of file system designs) represent facilities of this type. This paper utilizes the FOREM model as the principal tool and presents a hypothetical design example dealing with many essential issues of the design process. Evaluation of designs of several other actual file systems are also being carried out and will be reported at a later date. Only through quantitative evaluation can each design decision be arrived at correctly and the possible tradeoffs be identified.