scholarly journals An Ontology-Driven Personalized Faceted Search for Exploring Knowledge Bases of Capsicum

2021 ◽  
Vol 13 (7) ◽  
pp. 172
Author(s):  
Zaenal Akbar ◽  
Hani Febri Mustika ◽  
Dwi Setyo Rini ◽  
Lindung Parningotan Manik ◽  
Ariani Indrawati ◽  
...  
Keyword(s):  
Knowledge Sharing ◽  
Knowledge Base ◽  
Search Algorithm ◽  
Knowledge Bases ◽  
Raw Material ◽  
Potential Contribution ◽  
Knowledge Based Systems ◽  
Faceted Search ◽  
Knowledge Based ◽  
The Subject

Capsicum is a genus of flowering plants in the Solanaceae family in which the members are well known to have a high economic value. The Capsicum fruits, which are popularly known as peppers or chili, have been widely used by people worldwide. It serves as a spice and raw material for many products such as sauce, food coloring, and medicine. For many years, scientists have studied this plant to optimize its production. A tremendous amount of knowledge has been obtained and shared, as reflected in multiple knowledge-based systems, databases, or information systems. An approach to knowledge-sharing is through the adoption of a common ontology to eliminate knowledge understanding discrepancy. Unfortunately, most of the knowledge-sharing solutions are intended for scientists who are familiar with the subject. On the other hand, there are groups of potential users that could benefit from such systems but have minimal knowledge of the subject. For these non-expert users, finding relevant information from a less familiar knowledge base would be daunting. More than that, users have various degrees of understanding of the available content in the knowledge base. This understanding discrepancy raises a personalization problem. In this paper, we introduce a solution to overcome this challenge. First, we developed an ontology to facilitate knowledge-sharing about Capsicum to non-expert users. Second, we developed a personalized faceted search algorithm that provides multiple structured ways to explore the knowledge base. The algorithm addresses the personalization problem by identifying the degree of understanding about the subject from each user. In this way, non-expert users could explore a knowledge base of Capsicum efficiently. Our solution characterized users into four groups. As a result, our faceted search algorithm defines four types of matching mechanisms, including three ranking mechanisms as the core of our solution. In order to evaluate the proposed method, we measured the predictability degree of produced list of facets. Our findings indicated that the proposed matching mechanisms could tolerate various query types, and a high degree of predictability can be achieved by combining multiple ranking mechanisms. Furthermore, it demonstrates that our approach has a high potential contribution to biodiversity science in general, where many knowledge-based systems have been developed with limited access to users outside of the domain.

Knowledge Extraction from Domain-Specific Documents

2017 ◽  
pp. 106-123
Author(s):  
Ram Kumar ◽  
Shailesh Jaloree ◽  
R. S. Thakur
Keyword(s):  
Knowledge Representation ◽  
Knowledge Base ◽  
Knowledge Bases ◽  
Domain Ontology ◽  
Knowledge Based Systems ◽  
Domain Specific ◽  
Knowledge Based ◽  
Representation Systems ◽  
Terminological Confusion ◽  
Knowledge Representation Systems

Knowledge-based systems have become widespread in modern years. Knowledge-base developers need to be able to share and reuse knowledge bases that they build. As a result, interoperability among different knowledge-representation systems is essential. Domain ontology seeks to reduce conceptual and terminological confusion among users who need to share various kind of information. This paper shows how these structures make it possible to bridge the gap between standard objects and Knowledge-based Systems.

scholarly journals Knowledge-Based Systems Manufacturing With Viability Ensuring

2021 ◽  
Author(s):  
Valeriya V. Gribova ◽  
Elena A. Shalfeeva
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Base ◽  
Product Family ◽  
Knowledge Bases ◽  
Knowledge Based Systems ◽  
Manufacturing Environment ◽  
Development Environment ◽  
Systematic Analysis ◽  
Knowledge Based ◽  
Medical Software

Abstract With highly increased competition, intelligent product manufacturing based on interpretable knowledge bases has been recognized as an effective method for building applications of explainable Artificial Intelligence that is the hottest topic in the field of Artificial Intelligence. The success of product family directly depends on how effective the viability mechanisms are laid down in its design. In this paper, a systematic cloud-based set of tool family is proposed to develop viable knowledge-based systems. For productive participation of domain and cognitive specialists in manufacturing, the knowledge base should be declarative, testable and integratable with other architectural components. Mechanisms to ensure KBS viability are provided in an ontology-oriented development environment, where each component is formed in terms of domain ontology by using the adaptable instrumental support. Due to the explicit separation of ontology from knowledge, it became possible to divide competencies between specialists creating an ontology and specialists creating a knowledge base. We rely on the fact that the activity of creating an ontology is significantly different from the activity of creating a knowledge base. Creating an ontology is a creative process that requires a systematic analysis of the domain area in order to identify common patterns among its knowledge.The characteristic properties of knowledge-based systems related to viability are described. It is explained, how these properties are provided in development environments implemented on cloud platform. The concept of a specialized manufacturing environment for knowledge-based system is introduced. The necessary set of tools for such ontology-oriented environment construction is determined. The example of tools for creating specialized manufacturing environments is the instruments implemented on the «IACPaaS» platform. The IACPaaS is already used for collective development of thematic cloud knowledge portals with viable knowledge-based systems. This specialized manufacturing environment has enabled the creation of multi-purpose medical software services to support specialist solutions based on knowledge being remotely improved by experts.

scholarly journals Supporting Creative Mechanical Design

1994 ◽  
Author(s):  
Kun Sun ◽  
Boi Faltings
Keyword(s):  
Mechanical Design ◽  
Knowledge Bases ◽  
Creative Design ◽  
Knowledge Based Systems ◽  
Cad Systems ◽  
Knowledge Based ◽  
Logical Language ◽  
Promising Application ◽  
Qualitative Physics ◽  
And Function

Abstract Knowledge-based CAD systems limit designers’ creativity by constraining them to work with the prototypes provided by the systems’ knowledge bases. We investigate knowledge-based CAD systems capable of supporting creative designs in the example domain of elementary mechanisms. We present a technique based on qualitative explanations which allows a designer to extend the knowledge base by demonstrating a structure which implements a function in a creative way. Structure is defined as the geometry of the parts, and function using a general logical language based on qualitative physics. We argue that the technique can accommodate any creative design in the example domain, and we demonstrate the technique using an example of a creative design. The use of qualitative physics as a tool for extensible knowledge-based systems points out a new and promising application area for qualitative physics.

OPGEN: A System to Identify and Evaluate Potential Applications of Knowledge Based Systems

1992 ◽  
Author(s):  
Samir Rohatgi ◽  
James H. Oliver ◽  
Stuart S. Chen
Keyword(s):  
Knowledge Acquisition ◽  
Knowledge Base ◽  
Knowledge Based Systems ◽  
The Core ◽  
Knowledge Based ◽  
Evaluation Functions ◽  
Potential Applications ◽  
Computer Based ◽  
Suitable System ◽  
Overall Effectiveness

Abstract This paper describes the development of OPGEN (Opportunity Generator), a computer based system to help identify areas where a knowledge based system (KBS) might be beneficial, and to evaluate whether a suitable system could be developed in that area. The core of the system is a knowledge base used to carry out the identification and evaluation functions. Ancillary functions serve to introduce and demonstrate KBS technology to enhance the overall effectiveness of the system. All aspects of the development, from knowledge acquisition through to testing are presented in this paper.

A Knowledge-Based Approach to Modelling of Robotic Assembly Cells

Robotica ◽  
1991 ◽  
Vol 9 (1) ◽  
pp. 31-42 ◽  
Author(s):  
Dae-Won Kim ◽  
Bum-Hee Lee ◽  
Myoung-Sam Ko
Keyword(s):  
Knowledge Base ◽  
State Transition ◽  
Knowledge Bases ◽  
The State ◽  
System Structure ◽  
Robotic Assembly ◽  
Knowledge Based ◽  
Job Information ◽  
Assembly Cell ◽  
Transition Map

SUMMARYIn this paper, an approach to modelling of a robotic assembly cell is proposed and a method for managing the cell operation is described using a knowledge base. Since the modelling structure is based on the concept of the state variable, the relationships between states are described by the state transition map (STM). The knowledge-bases for state transition and assembly job information are obtained from the STM and the assembly job tree (AJT), respectively. Using the knowledge-base, the System structure is discussed in relation to both managing the cell operation and evaluating the performances. Finally, a simulation algorithm is presented with the simulation results to show the significance of the proposed modelling approach.

Altering the SightPlan knowledge-based systems

1992 ◽  
Vol 6 (1) ◽  
pp. 19-37 ◽  
Author(s):  
I. D. Tommelein ◽  
B. Hayes-Roth ◽  
R. E. Levitt
Keyword(s):  
Problem Solving ◽  
Knowledge Bases ◽  
Knowledge Based Systems ◽  
Knowledge Domain ◽  
Task Knowledge ◽  
Knowledge Based ◽  
Site Layout ◽  
Different Types ◽  
Control Knowledge ◽  
Construction Site Layout

SightPlan refers to several knowledge-based systems that address construction site layout. Five different versions were implemented and their components of expertise are described here. These systems are alterations of one another, differing either in the problems they solve, the problem-solving methods they apply, or the tasks they address. Because they share either control knowledge, domain concepts, or heuristics, and such knowledge is implemented in well-defined modular knowledge bases, these systems could easily re-use parts of one another. Experiments like those presented here may clarify the role played by different types of knowledge during problem solving, enabling researchers to gain a broader understanding of the generality of the domain and task knowledge that is embedded in KBSs and of the power of their systems.

AN ACTIVE DATABASE APPROACH TO CONSISTENCY MANAGEMENT IN DATA- AND KNOWLEDGE-BASED SYSTEMS

1993 ◽  
Vol 02 (02) ◽  
pp. 187-200 ◽  
Author(s):  
LEONARD J. SELIGMAN ◽  
LARRY KERSCHBERG
Keyword(s):  
Knowledge Base ◽  
Knowledge Bases ◽  
Simple Extension ◽  
Active Databases ◽  
New Approach ◽  
Consistency Management ◽  
Knowledge Based ◽  
Consistency Constraints ◽  
Consistency Problem ◽  
Representation Language

Many AI and other applications populate their knowledge-bases with information retrieved from large, shared databases. This paper describes a new approach to maintaining consistency between objects in dynamic, shared databases and copies of those objects which are cached in an application knowledge-base. The approach relies on an intelligent interface to active databases that we call a Mediator for Approximate Consistency (MAC). The MAC has several unique features: (1) it permits applications to specify their consistency requirements declaratively, using a simple extension of a frame-based representation language, (2) it automatically generates the interfaces and database objects necessary to enforce those consistency requirements, shielding the knowledge-base developer from the implementation details of consistency maintenance, and (3) it provides an explicit representation of consistency constraints in the database, which allows them to be queried and reasoned about. The paper describes the knowledge-base/database consistency problem and previous approaches to dealing with it. It then describes our architecture for maintaining approximate knowledge-base/database consistency, including techniques for specifying, representing, and enforcing consistency constraints.

scholarly journals Ontologies for supporting engineering analysis models

2005 ◽  
Vol 19 (1) ◽  
pp. 1-18 ◽  
Author(s):  
IAN R. GROSSE ◽  
JOHN M. MILTON–BENOIT ◽  
JACK C. WILEDEN
Keyword(s):  
Knowledge Sharing ◽  
Knowledge Base ◽  
Knowledge Exchange ◽  
Engineering Analysis ◽  
Report Generation ◽  
Knowledge Based ◽  
Computational Environment ◽  
Object Inspection ◽  
Expertise Level ◽  
Analysis Models

In this paper we lay the foundations for exchanging, adapting, and interoperating engineering analysis models (EAMs). Our primary foundation is based upon the concept that engineering analysis models are knowledge-based abstractions of physical systems, and therefore knowledge sharing is the key to exchanging, adapting, and interoperating EAMs within or across organizations. To enable robust knowledge sharing, we propose a formal set of ontologies for classifying analysis modeling knowledge. To this end, the fundamental concepts that form the basis of all engineering analysis models are identified, described, and typed for implementation into a computational environment. This generic engineering analysis modeling ontology is extended to include distinct analysis subclasses. We discuss extension of the generic engineering analysis modeling class for two common analysis subclasses: continuum-based finite element models and lumped parameter or discrete analysis models. To illustrate how formal ontologies of engineering analysis modeling knowledge might facilitate knowledge exchange and improve reuse, adaptability, and interoperability of analysis models, we have developed a prototype engineering analysis modeling knowledge base, called ON-TEAM, based on our proposed ontologies. An industrial application is used to instantiate the ON-TEAM knowledge base and illustrate how such a system might improve the ability of organizations to efficiently exchange, adapt, and interoperate analysis models within a computer-based engineering environment. We have chosen Java as our implementation language for ON-TEAM so that we can fully exploit object-oriented technology, such as object inspection and the use of metaclasses and metaobjects, to operate on the knowledge base to perform a variety of tasks, such as knowledge inspection, editing, maintenance, model diagnosis, customized report generation of analysis models, model selection, automated customization of the knowledge interface based on the user expertise level, and interoperability assessment of distinct analysis models.

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