281,145 research outputs found

    A storage and access architecture for efficient query processing in spatial database systems

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    Due to the high complexity of objects and queries and also due to extremely large data volumes, geographic database systems impose stringent requirements on their storage and access architecture with respect to efficient query processing. Performance improving concepts such as spatial storage and access structures, approximations, object decompositions and multi-phase query processing have been suggested and analyzed as single building blocks. In this paper, we describe a storage and access architecture which is composed from the above building blocks in a modular fashion. Additionally, we incorporate into our architecture a new ingredient, the scene organization, for efficiently supporting set-oriented access of large-area region queries. An experimental performance comparison demonstrates that the concept of scene organization leads to considerable performance improvements for large-area region queries by a factor of up to 150

    Object-oriented querying of existing relational databases

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    In this paper, we present algorithms which allow an object-oriented querying of existing relational databases. Our goal is to provide an improved query interface for relational systems with better query facilities than SQL. This seems to be very important since, in real world applications, relational systems are most commonly used and their dominance will remain in the near future. To overcome the drawbacks of relational systems, especially the poor query facilities of SQL, we propose a schema transformation and a query translation algorithm. The schema transformation algorithm uses additional semantic information to enhance the relational schema and transform it into a corresponding object-oriented schema. If the additional semantic information can be deducted from an underlying entity-relationship design schema, the schema transformation may be done fully automatically. To query the created object-oriented schema, we use the Structured Object Query Language (SOQL) which provides declarative query facilities on objects. SOQL queries using the created object-oriented schema are much shorter, easier to write and understand and more intuitive than corresponding S Q L queries leading to an enhanced usability and an improved querying of the database. The query translation algorithm automatically translates SOQL queries into equivalent SQL queries for the original relational schema

    KOMBASE - a knowledge representation system with frames for an object-oriented knowledge base

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    Knowledge representation is an important area of research which is currently being done in the field of Artificial Intelligence (AI). In order to manipulate the wealth of information available in a typical AI application, mechanisms must be provided to represent and to reason with knowledge at a high level of abstraction. Knowledge representation with frames is a structured and object-oriented approach to this problem. KOMBASE is a prototype to a frame-based system containing organizational information of companies and other corporate bodies. This paper describes the approach adopted in the development of KOMBASE and discusses its implementation, particularly from a knowledge representational perspective
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