scholarly journals A Knowledge-based Method of Multilevel Query in Relational Database

2012 ◽  
Author(s):  
Jingke Xu ◽  
Huanliang Sun ◽  
Yonghui Wang ◽  
Xiaoyu Song ◽  
Shoujin Wang
Keyword(s):  
Relational Database ◽  
Knowledge Based

Research to Safety Evaluation Expert System of Hydraulic Engineering Metal Structures

2011 ◽  
Vol 48-49 ◽  
pp. 994-1001 ◽  
Author(s):  
Guang Ming Yang
Keyword(s):  
Expert System ◽  
Relational Database ◽  
Domain Knowledge ◽  
Safety Evaluation ◽  
Database System ◽  
Base System ◽  
Metal Structures ◽  
Knowledge Based ◽  
Knowledge Base System ◽  
Method Base

Combining the successful applications in AI, in this paper, an expert system is studied and designed for evaluating the safety of hydraulic metal structures, whose goal is compute the reliability of hydraulic metal structures. Applying the techniques of AI, a framework is made up for evaluating the safety of hydraulic metal structures. The framework of knowledge base system is designed and presented with the domain knowledge. Based on the theory of relational database, the conceptual and logical views of database system are designed and analysed. Additionally, method base system is designed. A practical example is given to illustrate the process of using this system. This system has features of practical and advanced and expand.

A KNOWLEDGE-BASED APPROACH TO COOPERATIVE RELATIONAL DATABASE QUERYING

2000 ◽  
Vol 14 (01) ◽  
pp. 73-90 ◽  
Author(s):  
JOSÉ LUÍS BRAGA ◽  
ALBERTO H. F. LAENDER ◽  
CLAUDINEY VANDER RAMOS
Keyword(s):  
Artificial Intelligence ◽  
Relational Database ◽  
Knowledge Bases ◽  
Application Domain ◽  
Query Formulation ◽  
Database Querying ◽  
Artificial Intelligence Techniques ◽  
Knowledge Based

We present in this paper an approach to providing cooperativeness in database querying using artificial intelligence techniques. The main focus is a cooperative interface that assists nonexperienced and casual users in extracting useful answers from a relational database. Our approach relies on an architecture that comprises two knowledge bases which store rules that describe the application domain and guide the process of query formulation and answering. A subset of SQL is used for expressing queries, and the cooperative interface relieves the user from knowing its full syntax and the structure of the database.

scholarly journals Storing an OWL 2 Ontology in a Relational Database Structure

2015 ◽  
Vol 3 ◽  
pp. 71 ◽  
Author(s):  
Henrihs Gorskis ◽  
Arkady Borisov
Keyword(s):  
Relational Database ◽  
Domain Ontology ◽  
Database Management System ◽  
Software Library ◽  
Software Libraries ◽  
Knowledge Based ◽  
Ontology Language ◽  
Database Structure ◽  
Rdf Data ◽  
Language Specification

<p class="R-AbstractKeywords"><span lang="EN-GB">This paper examines the possibility of storing OWL 2 based ontology information in a classical relational database and reviews some existing methods for ontology databases. In most cases a database is a fitting solution for storing and sharing information among systems, clients or agents. Similarly, in order to make domain ontology information more accessible to systems, in a comparable way, it can be stored and provided in a database form. As of today, there is no consensus on a specific ontology database structure. The main focus of this paper is specifically on OWL 2 as a basis for the description of ontology centric information in a database. The Web Ontology Language OWL 2 is a language for describing ontology information for the Semantic Web. As such it consists of a list of reserved words and grammatical rules for defining many parts of ontology knowledge. Based on this language specification this paper examines the possibility of storing information in a relational database for the description of domain ontology information. By creating a database structure based on OWL2 it is feasible to obtain an approach to storing information about the domain ontology in an utilizable way, by using its descriptive abilities. Nowadays multiple approaches to storing ontology information and OWL in databases exist; most of them are based on storing RDF data or provide persistence for specific OWL software libraries. The examination of the existing approaches provided in this paper, shows how they differ from the goal of obtaining a general, more easily usable and less software library specific database for domain ontology centric information. This paper describes a version of a simple relational database capable of holding and providing ontology knowledge on demand, which can be implemented on a database management system of choice. </span></p>

Interfacing a knowledge-based system to a large database

1989 ◽  
Vol 4 (1) ◽  
pp. 31-51 ◽  
Author(s):  
P. M. D. Gray ◽  
I. G. Archibald ◽  
K. Lunn
Keyword(s):  
Expert System ◽  
Relational Database ◽  
Large Database ◽  
End User ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
Product Formulation ◽  
Front End ◽  
Mainframe Computer

AbstractThis paper describes the interfacing problem that arose in a Product Formulation expert system written in LISP that had to be interfaced to data in a relational database running on a separate mainframe computer. It surveys the different forms of coupling that are possible and emphasizes the advantages of tight navigational coupling over the more popular set-based coupling. It describes how Prolog was used to overcome the interfacing problems and to provide a customized front end to an end user, based on a navigational interface. It reviews the techniques of using Prolog and the likely obstacles, together with a look forward to databases using Frames or Objects.

BUILDING A FEDERATED RELATIONAL DATABASE SYSTEM: AN APPROACH USING A KNOWLEDGE-BASED SYSTEM

1994 ◽  
Vol 03 (04) ◽  
pp. 415-455 ◽  
Author(s):  
JOSÉ MIGUEL BLANCO ◽  
ARANTZA ILLARRAMENDI ◽  
ALFREDO GOÑI
Keyword(s):  
Relational Database ◽  
Relational Databases ◽  
Database System ◽  
Integration Process ◽  
Representation System ◽  
Relational Schema ◽  
Knowledge Based ◽  
Relational Database System ◽  
Knowledge Representation System ◽  
Data Elements

Due to the emerging interest in integrating different application environments, there have been many recent proposals for federated systems. In this paper, a federated system that permits the integration of heterogeneous relational databases using a terminological knowledge representation system is presented. In particular, two of the system's components: the translator and the integrator are explained in depth. The translator permits one to obtain a terminology from a relational schema, either semiautomatically, by expressing database properties, or manually, by using a set of predefined operations. In turn, the integrator generates a federated terminology by integrating several terminologies using the semantics expressed as correspondences between the data elements of different terminologies. Unlike many other approaches, the use of a terminological system permits us to obtain a semantically richer federated terminology and, at the same time, define a wider and more consistent integration process.

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