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This paper investigates cyclic query processing issues in objectoriented databases. We first define a data and cyclic query model for an object-oriented database system using a graph model. We then discuss the efficient processing of a general object-oriented cyclic query. For efficient processing, we first define a general cyclic query, the access plans generated for a given query, then develop a cost model to determine the cost for each access plan generated. We also investigate the retrieval algorithms used for actual data retrieval. [i] INTRODUCTIONObject-oriented databases have recently become a very active research area. Several projects on object-oriented databases are mentioned in [DITT86]. Object-oriented database systems research are attempts to overcome the rather limited modelling capabilities that are provided by traditional database systems. These traditional systems are not well-suited to handling advanced applications like CAD/CAM design, office automation, VLSI design and AI applications among others. Object-oriented database systems have the capabilities to handle the complex applications mentioned above by supporting complex data types, generalization/specialization abstraction and aggregation abstraction among others.This paper investigates query processing issues in object-oriented databases. Specifically we are interested in efficient processing of cyclic queries. Query processing issues in an object-oriented database bring out many of the same issues as in conventional databases. One issue in objectoriented query processing is the order in which classes involved in a query must be evaluated. This is similar to the order in which the relations involved in a join must be evaluated in relational databases and the order in which record @pes are visited in evaluating a query in network databases.Query processing involves the following three elements.Identify the class of cyclic queries to consider. Identify all access plans for a given query. Estimate the cost of each access plan and select reasonable access plans for a given query.(1) (2) (3)Most research in cyclic query processing has focused on recursive query processing and optimization in relational and logic databases. In general, the solution to a recursive query cannot be expressed as a finite relational algebraic expression and therefore cannot be evaluated directly by a conventional relational database system. One approach to solve this problem is to provide an appropriate interface between PROLOG and a relational database system [JARK84]; while others provide some means of recursion to overcome the limitations of relationally complete query languages [KERS84, JARK85.LINN861. The optimization techniques for this kind of recursion can be found in [BANC86, ULLM85, GARD861. The above solutions are for conventional systems using flat tables. LJNN871shows that this is cumbersome for the user as well as for the optimization of recursive queries and proposes a better solution combining the non-first normal form relation model with a recurs...

The paper describes a computational procedure for defining associations between words used to index a collection of documents. Using association structures generated by the procedure in a small document col-This paper describes experiments with a statistical technique that can be iised to compute word associations 119eful for document retrieval purposes in a collection where documents are described by index words occurring in the tcst or in abstracts of the documcnts.Although the experiments have been conducted with a small collection of documents, they have suggested methods that will permit the association technique to be applied in collections of an interesting size. This is important, since a number of alternative methods that have been proposed for computing word associations appear to present intractable computation problems that \vill deter large scale application. Why Associative Retrieval?There :ire three principal reasons why associative 1. The efficiency of retrieval in a coordinate indexed system rapidly diminishes as the document collection grows in size, I n an associative retrieval system, on the other hand, retrieval efficiency as measured by recall and relevance ratios will not necessarily decrease with the size of the document collection, and might, in fact, improve ( 1 ) . 2. If the structure of word associations in a given collection is adequate, the user of the collection can define a retrieval request in his own terms without reference to an elaborate dictionary or thesaurus of index terms. Thus, the need for interposing an interpreter between the user and the collection e m be dispensed with, and the ex-retrieval techniques are worth investigating:lection, a retrieval model is described and the results of trial retrievals are evaluated. The techniques described appear to be applicable in practice for retrieval in large collections.ponentially increasing difficulty of compiling an external thesaurus is avoided. 3. The techniques can be applied to word data that has been automatically processed from document tests, or identified in texts by individuals inesperienced in complex conventional indexing methods, thus permitting rapid indexing and acquisition of materials in a collection. Clumping Techniques and Word AssociationsThe method used to define word associations is based' on the theory of clumps (2,3,4,5), a technique developed largely by R. M. Needham of the Cambridge Language Research Unit. The notion of a clump is intuitively simple: a clump is a group of objects from some universe of objects such that the members of the group (tech. nically, the nibset) are more closely related to each other than to the rest of the universe to which they belong.I n order to find clumps of objects, two decisions must first be made: 1. We have to specify how associations between objects are to be measured. 2.We have to specify the criteria that define a clump.

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Current developments m database management technology m the USSR are reviewed in the framework of the Soviet computing environment and the classes of information processing systems under development. The characteristms of operational and experimental Soviet database management systems are examined, and current research m the USSR on database management and related software topms is reviewed.