Design and implementation of domain ontology-based oilfield non-metallic pipe information retrieval system

2012 ◽  
Author(s):  
Rong Guo ◽  
Jun Wu
Keyword(s):  
Information Retrieval ◽  
Retrieval System ◽  
Domain Ontology ◽  
Information Retrieval System ◽  
Design And Implementation

A Database Project in a Small Company (or How the Real World Doesn't Always Follow the Book)

2009 ◽  
pp. 468-483
Author(s):  
Efrem Mallach
Keyword(s):  
Information Retrieval ◽  
Real World ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Small Company ◽  
The Real ◽  
Design And Implementation ◽  
Development Methods

The case study describes a small consulting company’s experience in the design and implementation of a database and associated information retrieval system. Their choices are explained within the context of the firm’s needs and constraints. Issues associated with development methods are discussed, along with problems that arose from not following proper development disciplines.

Research on Domain Ontology-Based Intelligent Information Retrieval System

2011 ◽  
Vol 460-461 ◽  
pp. 300-304
Author(s):  
Shu Dong Zhang ◽  
Yan Chen
Keyword(s):  
Information Retrieval ◽  
Retrieval System ◽  
Rapid Development ◽  
Relevant Information ◽  
Domain Ontology ◽  
Information Retrieval System ◽  
Information Resources ◽  
Semantic Level ◽  
Intelligent Information Retrieval ◽  
Intelligent Information

Domain ontology introduces a new theory and method for information retrieval. In this paper, we analyze the deficiencies of traditional information retrieval and explore the relationship between domain ontology and information retrieval, as well as the basic design ideas of information retrieval based on domain ontology. Finally we present a domain ontology-based intelligent information retrieval system, so that the information retrieval can be promoted from the keyword level to the semantic level. With the rapid development of the national economy and the growth of information resources, traditional methods relying on the browser, database fields, keyword matching, or even manual retrieval query has become increasingly difficult to meet people's information retrieval needs. How to quickly and accurately identify the needed information resources has become a urgent question in front of us. Information retrieval is a technology which can find out the relevant information the user needs from a collection of large amounts of information. It has experienced manual retrieval, computer retrieval stage, now it has developed to the network and intelligent stage. The objects of information retrieval extend from a relative closed, stable and consistent, centrally managed information content by an independent database to an open, dynamic, quickly update, widely distributed, and loosely managed web content; the users of information retrieval also spread from professional intelligence agent to the common including government officials, businessmen, managers, teachers, students, professionals, etc. They ask for the higher and more diverse requirements from the results to the manner of information retrieval. Adapting to the need for network, intelligence and personalization is a new trend of information retrieval technology.

scholarly journals An Ontology Based Information Retrieval System

2020 ◽  
Vol 9 (2) ◽  
pp. 638-643
Keyword(s):  
Information Retrieval ◽  
Query Expansion ◽  
Retrieval System ◽  
Keyword Search ◽  
Domain Ontology ◽  
Information Retrieval System ◽  
Search System ◽  
Domain Specific ◽  
System A ◽  
Schema Graph

Ontology provide a structured way of describing knowledge. Ontology's are usually repositories of concepts and relations between them, so using them in information retrieval seems to be a reasonable goal. The main objective in this report is to provide efficient means to move from keyword-based to concept-based information retrieval utilizing ontology's for conceptual definitions [1]. In this paper, we present the skeleton of such an IR system which works on a collection of domain specific documents and exploits the use of a domain specific ontology to improve the overall number of relevant documents retrieved. In this system, a user enters a query from which the meaningful concepts are extracted; using these concepts and domain ontology, query expansion is performed. We propose a system that matches the query terms in the ontology/schema graph and exploits the surrounding knowledge to derive an enhanced query. The enhanced query is given to the underlying basic keyword search system LUCENE [2]. In this approach we try to make use of more ontological Knowledge than IS-A and HAS-A relationships and synonyms for information retrieval.

IMAGE RETRIEVAL USING FUZZY EVALUATION OF COLOR SIMILARITY

1994 ◽  
Vol 08 (04) ◽  
pp. 945-968 ◽  
Author(s):  
ELISABETTA BINAGHI ◽  
ISABELLA GAGLIARDI ◽  
RAIMONDO SCHETTINI
Keyword(s):  
Information Retrieval ◽  
Set Theory ◽  
Fuzzy Set Theory ◽  
Retrieval System ◽  
Color Image ◽  
Information Retrieval System ◽  
Fuzzy Evaluation ◽  
Retrieval Strategy ◽  
Design And Implementation ◽  
Color Similarity

The paper describes the design and implementation of an information retrieval system using color as the index in its color image archive. Salient aspects of this approach are the use of direct visual representation of color in querying and of fuzzy set theory to formally represent intrinsic human uncertainty in evaluating the similarity between colors (query interpretation). The steps in which the information retrieval strategy is organized are illustrated, and an example of its application given, showing how the implemented system can be tailored to manage archives of images representing fabric samples.

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