scholarly journals Fuzzy Ontology-Based Querying User' Requests Under Uncertain Environment

2020 ◽  
Vol 14 (3) ◽  
pp. 41-59 ◽  
Author(s):  
Mohamed Nazih Omri
Keyword(s):  
Semantic Network ◽  
Knowledge Extraction ◽  
Experimental Results ◽  
Novice User ◽  
Uncertain Environment ◽  
Automatic Construction ◽  
Fuzzy Ontology ◽  
Uncertain Knowledge

Assistance with the use of technical devices is required as soon as the tasks to be performed become complex. This assistance is also needed as soon as the authors provide assistance to users to find solutions to incidents that occur during the application of unsuitable procedures. The goal of this work is then to provide a knowledge extraction approach that can interpret user requests into valid system requests to respond appropriately to novice user requests. This approach is based on a fuzzy semantic network for the modeling of imprecise and uncertain knowledge and the automatic construction of temporary fuzzy ontology for the identification and interpretation of user requests. The proposed approach has the advantage of being able to integrate the notion of uncertain and imprecise knowledge into the representation of system objects and procedures. The experimental results show the efficiency and the effectiveness of the approach.

scholarly journals MalayIK: An Ontological Approach to Knowledge Transformation in Malay Unstructured Documents

2018 ◽  
Vol 8 (1) ◽  
pp. 1 ◽  
Author(s):  
Fatimah Sidi ◽  
Iskandar Ishak ◽  
Marzanah A. Jabar
Keyword(s):  
Knowledge Base ◽  
Data Extraction ◽  
Knowledge Extraction ◽  
Experimental Results ◽  
New Approach ◽  
Knowledge Transformation ◽  
Ontological Approach ◽  
Automatic Systems ◽  
Existing Data ◽  
The Web

The number of unstructured documents written in Malay language is enormously available on the web and intranets. However, unstructured documents cannot be queried in simple ways, hence the knowledge contained in such documents can neither be used by automatic systems nor could be understood easily and clearly by humans. This paper proposes a new approach to transform extracted knowledge in Malay unstructured document using ontology by identifying, organizing, and structuring the documents into an interrogative structured form. A Malay knowledge base, the MalayIK corpus is developed and used to test the MalayIK-Ontology against Ontos, an existing data extraction engine. The experimental results from MalayIK-Ontology have shown a significant improvement of knowledge extraction over Ontos implementation. This shows that clear knowledge organization and structuring concept is able to increase understanding, which leads to potential increase in sharable and reusable of concepts among the community.

Fuzzy Ontology-Based Approach for Automatic Construction of User Profiles

2014 ◽  
pp. 339-346
Author(s):  
Mateus Ferreira-Satler ◽  
Francisco P. Romero ◽  
Jose A. Olivas ◽  
Jesus Serrano-Guerrero
Keyword(s):  
User Profiles ◽  
Automatic Construction ◽  
Fuzzy Ontology

Research on Automatic Construction of Financial Ontology Using Chinese Encyclopedia Resource

2013 ◽  
Vol 765-767 ◽  
pp. 1240-1244
Author(s):  
Qian Mo ◽  
Shu Zhang
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Management ◽  
Information Retrieval ◽  
Semantic Web ◽  
Large Scale ◽  
Semantic Information ◽  
Dominant Role ◽  
Experimental Results ◽  
Automatic Construction ◽  
Scale Creation

Ontology plays a dominant role in a growing number of different fields, such as information retrieval, artificial intelligence, semantic Web and knowledge management, etc. However, manual construction of large ontology is not feasible. This article discusses how to create Financial Ontology automatically from a resource of Chinese Encyclopedia. Financial Ontology includes Is-A relationship, Class-Instance relationship, Attribute-of relationship and Synonym relationship. Experimental Results show us that the constructed Financial Ontology has great advantages in the large scale, creation cost and the richness of semantic information.

scholarly journals Knowledge Extraction and Discovery Based on BIM: A Critical Review and Future Directions

2021 ◽  
Author(s):  
Zhen-Zhong Hu ◽  
Shuo Leng ◽  
Jia-Rui Lin ◽  
Sun-Wei Li ◽  
Ya-Qi Xiao
Keyword(s):  
Semantic Network ◽  
Knowledge Extraction ◽  
Information Modeling ◽  
Knowledge Map ◽  
Future Directions ◽  
Knowledge Application ◽  
Building Information ◽  
Construction Operation ◽  
Design Construction ◽  
Aec Industry

AbstractIn the past, knowledge in the fields of Architecture, Engineering and Construction (AEC) industries mainly come from experiences and are documented in hard copies or specific electronic databases. In order to make use of this knowledge, a lot of studies have focused on retrieving and storing this knowledge in a systematic and accessible way. The Building Information Modeling (BIM) technology proves to be a valuable media in extracting data because it provides physical and functional digital models for all the facilities within the life-cycle of the project. Therefore, the combination of the knowledge science with BIM shows great potential in constructing the knowledge map in the field of the AEC industry. Based on literature reviews, this article summarizes the latest achievements in the fields of knowledge science and BIM, in the aspects of (1) knowledge description, (2) knowledge discovery, (3) knowledge storage and management, (4) knowledge inference and (5) knowledge application, to show the state-of-arts and suggests the future directions in the application of knowledge science and BIM technology in the fields of AEC industries. The review indicates that BIM is capable of providing information for knowledge extraction and discovery, by adopting semantic network, knowledge graph and some other related methods. It also illustrates that the knowledge is helpful in the design, construction, operation and maintenance periods of the AEC industry, but now it is only at the beginning stage.

PERTINENT KNOWLEDGE EXTRACTION FROM A SEMANTIC NETWORK: APPLICATION OF FUZZY SETS THEORY

2004 ◽  
Vol 13 (03) ◽  
pp. 705-719 ◽  
Author(s):  
M. N. OMRI
Keyword(s):  
Fuzzy Sets ◽  
Semantic Network ◽  
Extraction Process ◽  
Knowledge Extraction ◽  
Fuzzy Sets Theory ◽  
Short Survey ◽  
Network Application ◽  
Sets Theory ◽  
Flexible Knowledge

In this paper we describe an approach to define flexible Knowledge Extraction Systems able to deal with the inherent vagueness and uncertainty of the Extraction process. We also present a short survey of fuzzy and semantic approaches to knowledge extraction. The goal of such approaches is to address if and how some approaches met their goal.

A Bayesian Network-Based Approach for Incremental Learning of Uncertain Knowledge

2018 ◽  
Vol 26 (01) ◽  
pp. 87-108 ◽  
Author(s):  
Weiyi Liu ◽  
Kun Yue ◽  
Mingliang Yue ◽  
Zidu Yin ◽  
Binbin Zhang
Keyword(s):  
Decision Making ◽  
Bayesian Network ◽  
Incremental Learning ◽  
Experimental Results ◽  
Hill Climbing ◽  
Uncertain Knowledge ◽  
Markov Equivalence ◽  
Influence Degree ◽  
Analysis Prediction

Bayesian network (BN) is the well-accepted framework for representing and inferring uncertain knowledge. To learn the BN-based uncertain knowledge incrementally in response to the new data is useful for analysis, prediction, decision making, etc. In this paper, we propose an approach for incremental learning of BNs by focusing on the incremental revision of BN’s graphical structures. First, we give the concept of influence degree to describe the influence of new data on the existing BN by measuring the variation of BN’s probability parameters w.r.t. the likelihood of the new data. Then, for the nodes ordered decreasingly by their influence degrees, we give the scoring-based algorithm for revising BN’s subgraphs iteratively by hill-climbing search for reversing, adding or deleting edges. In the incremental revision, we emphasize the preservation of probabilistic conditional independencies implied in the BN based on the concept and properties of Markov equivalence. Experimental results show the correctness, precision and efficiency of our approach.

Apply fuzzy ontology and FML to knowledge extraction for university governance and management

2012 ◽  
Vol 4 (4) ◽  
pp. 493-513 ◽  
Author(s):  
Che-Hung Liu ◽  
Chang-Shing Lee ◽  
Mei-Hui Wang ◽  
Yu-Yang Tseng ◽  
Yi-Ling Kuo ◽  
...  
Keyword(s):  
Knowledge Extraction ◽  
University Governance ◽  
Fuzzy Ontology

Diagnostics of Gold Laser Plasmas

1988 ◽  
Vol 102 ◽  
pp. 357-360
Author(s):  
J.C. Gauthier ◽  
J.P. Geindre ◽  
P. Monier ◽  
C. Chenais-Popovics ◽  
N. Tragin ◽  
...  
Keyword(s):  
Experimental Results ◽  
Pure Gold ◽  
Electronic Temperature ◽  
X Ray ◽  
Laser Plasmas ◽  
Collisional Radiative Model ◽  
Radiative Model

AbstractIn order to achieve a nickel-like X ray laser scheme we need a tool to determine the parameters which characterise the high-Z plasma. The aim of this work is to study gold laser plasmas and to compare experimental results to a collisional-radiative model which describes nickel-like ions. The electronic temperature and density are measured by the emission of an aluminium tracer. They are compared to the predictions of the nickel-like model for pure gold. The results show that the density and temperature can be estimated in a pure gold plasma.

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