An Environment for Multi-domain Ontology Development and Knowledge Acquisition

2002 ◽  
pp. 104-116 ◽  
Author(s):  
Jinxin Si ◽  
Cungen Cao ◽  
Haitao Wang ◽  
Fang Gu ◽  
Qiangze Feng ◽  
...  
Keyword(s):  
Knowledge Acquisition ◽  
Domain Ontology ◽  
Ontology Development

Research on Knowledge Discovery and Stock Forecasting of Financial News Based on Domain Ontology

2019 ◽  
Vol 18 (03) ◽  
pp. 953-979 ◽  
Author(s):  
Lingling Zhang ◽  
Minghui Zhao ◽  
Zili Feng
Keyword(s):  
Knowledge Acquisition ◽  
Knowledge Discovery ◽  
Tacit Knowledge ◽  
Explicit Knowledge ◽  
Academic Research ◽  
Online News ◽  
Domain Ontology ◽  
General Mechanism ◽  
Financial News ◽  
Knowledge Reasoning

In the era of big data, how to obtain useful knowledge from online news and utilize it as an important basis to make investment decision has become the hotspot of industrial and academic research. At present, there have been research and practice on explicit knowledge acquisition from news, but tacit knowledge acquisition is still under exploration. Based on the general mechanism of domain knowledge, knowledge reasoning, and knowledge discovery, this paper constructs a framework for discovering tacit knowledge from news and applying the knowledge to stock forecasting. The concrete work is as follows: First, according to the characteristics of financial field and the conceptual cube, the conceptual structure of industry–company–product is constructed, and the framework of domain ontology is put forward. Second, with the construction of financial field ontology, the financial news knowledge management framework is proposed. Besides, with the application of attributes in ontology and domain rules extracted from news text, the knowledge reasoning mechanism of financial news is constructed to achieve financial news knowledge discovery. Finally, news knowledge that reflects important information about stock changes is integrated into the traditional stock price forecasting model and the newly proposed model performs well in the empirical analysis of polyester industry.

scholarly journals SWRL: Rule Acquisition Using Ontology

2009 ◽  
Vol 40 (1) ◽  
pp. 117-122 ◽  
Author(s):  
Darya Plinere ◽  
Arkady Borisov
Keyword(s):  
Knowledge Acquisition ◽  
Main Issue ◽  
Ontology Development ◽  
Rule Based ◽  
Development Platform ◽  
Rule Acquisition ◽  
Rule System ◽  
Rule Based Systems

SWRL: Rule Acquisition Using Ontology Nowadays rule-based systems are very common. The use of ontology-based systems is becoming ever more popular, especially in addition to the rule-based one. The most widely used ontology development platform is Protégé. Protégé provides a knowledge acquisition tool, but still the main issue of the ontology-based rule system is rule acquisition. This paper presents an approach to using SWRL rules Tab, a plug-in to Protégé, for rule acquisition. SWRL rules Tab transforms conjunctive rules to Jess rules in IF…THEN form.

Ontological Conceptualization Based on the SKOS

2014 ◽  
Vol 14 (3) ◽  
Author(s):  
Farhad Ameri ◽  
Boonserm Kulvatunyou ◽  
Nenad Ivezic ◽  
Khosrow Kaikhah
Keyword(s):  
Domain Ontology ◽  
Knowledge Organization ◽  
Ontology Development ◽  
Stepping Stone ◽  
Simple Knowledge Organization System ◽  
Knowledge Organization System ◽  
Representation Formalism

Ontological conceptualization refers to the process of creating an abstract view of the domain of interest through a set of interconnected concepts. In this paper, a thesaurus-based methodology is proposed for systematic ontological conceptualization in the manufacturing domain. The methodology has three main phases, namely, thesaurus development, thesaurus evaluation, and thesaurus conversion and it uses simple knowledge organization system (SKOS) as the thesaurus representation formalism. The concept-based nature of a SKOS thesaurus makes it suitable for identifying important concepts in the domain. To that end, novel thesaurus evaluation and thesaurus conversion metrics that exploit this characteristic are presented. The ontology conceptualization methodology is demonstrated through the development of a manufacturing thesaurus, referred to as ManuTerms. The concepts in ManuTerms can be converted into ontological classes. The whole conceptualization process is the stepping stone to developing more axiomatic ontologies. Although the proposed methodology is developed in the context of manufacturing ontology development, the underlying methods, tools, and metrics can be applied to development of any domain ontology. The developed thesaurus can serve as a standalone lightweight ontology and its concepts can be reused by other ontologies or thesauri.

OMIT: Domain Ontology and Knowledge Acquisition in MicroRNA Target Prediction

2010 ◽  
pp. 1160-1167 ◽  
Author(s):  
Christopher Townsend ◽  
Jingshan Huang ◽  
Dejing Dou ◽  
Shivraj Dalvi ◽  
Patrick J. Hayes ◽  
...  
Keyword(s):  
Knowledge Acquisition ◽  
Target Prediction ◽  
Domain Ontology ◽  
Microrna Target ◽  
Microrna Target Prediction

Capturing Evolutional Knowledge Using Time Interval Tracing

2007 ◽  
Vol 11 (4) ◽  
pp. 373-380
Author(s):  
Shun-Chieh Lin ◽  
◽  
Chia-Wen Teng ◽  
Shian-Shyong Tseng ◽  
Keyword(s):  
Knowledge Acquisition ◽  
Knowledge Base ◽  
Time Domain ◽  
Domain Knowledge ◽  
Domain Ontology ◽  
Time Interval ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
Over Time

Knowledge acquisition is a critical bottleneck in building a knowledge-based system. Much research and many tools have been developed to acquire domain knowledge with embedded rules that may be ignored in constructing the initial prototype. Due to different backgrounds and dynamic knowledge changing over time, domain knowledge constructed at one time may be degraded at any time thereafter. Here, we propose knowledge acquisition, called enhanced embedded meaning capturing under uncertainty deciding (enhanced EMCUD), which constructs a domain ontology and traces information over time to efficiently update time-related domain knowledge based on the current environment. We enrich the knowledge base and ease the construction of domain knowledge that changes with times and the environment.

Knowledge Acquisition of Domain Ontology Based on the Documents

2013 ◽  
Vol 333-335 ◽  
pp. 2243-2247
Author(s):  
Zhao Qin Hu
Keyword(s):  
Knowledge Acquisition ◽  
Domain Knowledge ◽  
Domain Ontology ◽  
The Core ◽  
Core Concepts ◽  
Core Ontology ◽  
Text Preprocessing

In this paper we put forward the framework of domain knowledge acquisition based on the documents with the ontology theory and knowledge acquisition theory. We present four aspects of the framework for knowledge acquisition: establishing domain core ontology, text preprocessing, domain ontology knowledge acquisition and improving domain ontology. A core ontology is the core concepts and relationships of the domain area. Text preprocessing mainly analyzes and processes Chinese webpage to generate sets of words. Domain ontology knowledge acquisition parses the core ontology and completes concept matching and ontology editing. Improving domain ontology is to infer and evaluate core ontology expanded and make the ontology more scientific and reasonable. The proposed framework can be applied as a useful benchmark or guidance in domain knowledge acquisition.

scholarly journals OntoForInfoScience

2016 ◽  
Vol 10 (1) ◽  
Author(s):  
Fabrício Martins Mendonça ◽  
Maurício Barcellos Almeida
Keyword(s):  
Information Science ◽  
Domain Ontology ◽  
Knowledge Organization ◽  
Ontology Development ◽  
Blood Components ◽  
Development Cycle ◽  
Scientific Project ◽  
Per Se

Ontologies are instruments of knowledge organization that have been developed through several methodologies. These methodologies are well established, but their steps often are not well explained. Thus, only knowledge engineers are able to perform all steps required in the development of ontologies. Here, we describe a methodology that details each step of the ontology development cycle. The goal of this methodology - called OntoForInfoScience - is to overcome issues of technical jargon and logical-philosophical principles faced by experts in Knowledge Organization from the field of Information Science. These are the usual issues when one deals with and constructs ontologies. In order to identify those issues, our methodology was produced by information scientists during the development of ontology in the blood domain. This ontology, called Hemonto, is domain ontology about blood components under development within the scope of a scientific project. In this paper, we present a brief description of OntoForInfoScience, as well as the practical results of the development of the blood ontology. We conclude that the new methodology is useful for information scientists when creating formal ontological representations. In addition to the methodology per se, our research also provides partial results of the HEMONTO development.

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