Contextual knowledge representation, retrieval and interpretation in multimedia e-learning

2004 ◽  
Author(s):  
Weihong Huang ◽  
M.S. Hacid
Keyword(s):  
Knowledge Representation ◽  
Contextual Knowledge ◽  
E Learning

scholarly journals SEMANTIC AND CONTEXTUAL KNOWLEDGE REPRESENTATION USING INTER - LINGUA FOR AUTOMATED ASSESSMENT OF STRUCTURED C++ PROGRAM

2021 ◽  
Vol 9 (5) ◽  
pp. 185-188
Author(s):  
Maxwell Christian ◽  
◽  
Bhushan Trivedi , PhD ◽  
Keyword(s):  
Knowledge Representation ◽  
Automatic Evaluation ◽  
Patent Office ◽  
Contextual Knowledge ◽  
Automated Assessment ◽  
Standard Representation ◽  
Reference Number ◽  
The Subject ◽  
C Program ◽  
Contextual Binding

The process of automatic evaluation of a structured C++ program has the first and foremost requirement of specifying the developed structural C++ program in a standard, generalized and unified format. This generalized and standard representation of the program needs to incorporate the specification in terms of semantics as per the language features used and also the contextual binding in regards of the program definition as perceived and desired by the subject expert. Hence an inter - lingua which can represent the semantic and contextual knowledge of the developed structured C++ program will be the first and foremost requirement towards the process of automated assessment and grading of a structured C++ program.The work presented here is published for patent at Patent Office Branch, Mumbai, India with the reference number E-12/215/2021/MUM and application number 202121000796.

Adaptive Computation Paradigm in Knowledge Representation

2012 ◽  
pp. 142-156
Author(s):  
Marina L. Gavrilova
Keyword(s):  
Knowledge Representation ◽  
Software Systems ◽  
New Paradigm ◽  
Information System Design ◽  
Adaptive Computation ◽  
Data Intensive ◽  
Collaborative Environment ◽  
Adaptive Models ◽  
E Learning ◽  
Computational Sciences

The constant demand for complex applications, the ever increasing complexity and size of software systems, and the inherently complicated nature of the information drive the needs for developing radically new approaches for information representation. This drive is leading to creation of new and exciting interdisciplinary fields that investigate convergence of software science and intelligence science, as well as computational sciences and their applications. This survey article discusses the new paradigm of the algorithmic models of intelligence, based on the adaptive hierarchical model of computation, and presents the algorithms and applications utilizing this paradigm in data-intensive, collaborative environment. Examples from the various areas include references to adaptive paradigm in biometric technologies, evolutionary computing, swarm intelligence, robotics, networks, e-learning, knowledge representation and information system design. Special topics related to adaptive models design and geometric computing are also included in the survey.

Study on intelligent construction of English-Chinese bilingual context model based on CBR

2021 ◽  
pp. 1-8
Author(s):  
Yan Shi
Keyword(s):  
Second Language ◽  
Second Language Acquisition ◽  
Language Acquisition ◽  
Knowledge Representation ◽  
Implementation Process ◽  
Case Based Reasoning ◽  
Contextual Knowledge ◽  
Context Model ◽  
New Research ◽  
Reasoning Mechanism

The article briefly reviews the context-based view of the case-based reasoning mechanism and second language acquisition theories, and analyzes the feasibility of the application of CBR in bilingual context knowledge representation. Based on this, it proposes bilingualism. The computational model, algorithm and general implementation process of the system for contextual knowledge representation CBR system is a preliminary exploration of the application of machine learning and artificial intelligence theory in the study of second language acquisition theory. It is intended to provide a second language acquisition study to the new research methods and perspectives.

scholarly journals THE INFLUENCE MODEL OF KNOWLEDGE REPRESENTATION ON KNOWLEDGE QUALITY

2012 ◽  
Vol 5 (1) ◽  
pp. 30-36
Author(s):  
Valentyna Shvets
Keyword(s):  
Knowledge Representation ◽  
Intellectual Curiosity ◽  
Training Conditions ◽  
Influence Model ◽  
Learning Platform ◽  
Knowledge Quality ◽  
E Learning ◽  
Level Of Knowledge ◽  
The Brain ◽  
And Training

ABSTRACT The influence model of knowledge representation and training character testing in MOODLE on progress of students has been investigated in the article. The knowledge representation in the form of graphs and frames is able to raise the level of knowledge significantly. The using of the animation (in Flash and SketchUp) leads to better memorization of information owing subconscious reaction of students. The testing of students in training conditions of e-learning platform MOODLE makes more active the programme of the intellectual curiosity that is the function of the brain.

A Knowledge-Based Framework for E-Learning in Heterogeneous Pervasive Environments

2010 ◽  
pp. 20-41 ◽  
Author(s):  
Michele Ruta ◽  
Floriano Scioscia ◽  
Simona Colucci ◽  
Eugenio Di Sciascio ◽  
Tommaso Di Noia ◽  
...  
Keyword(s):  
Knowledge Representation ◽  
Learning Objects ◽  
General Purpose ◽  
Learning Approach ◽  
Learning Resources ◽  
Handheld Device ◽  
Knowledge Based ◽  
User Request ◽  
E Learning ◽  
Everyday Problems

We propose a ubiquitous learning approach useful not only to acquire knowledge in the traditional educational meaning, but also to solve cross-environment everyday problems. By formalizing user request and profile through logic-based knowledge representation languages, a lightweight but semantically meaningful matchmaking process is executed in order to retrieve the most suitable learning resources. Standard formats for distribution of learning objects is extended in a backward-compatible way to support semantic annotations in our framework. Framework and algorithms are absolutely general purpose, nevertheless an application has been developed where the semantic-based Bluetooth/RFID discovery protocols devised in previous work, support users –equipped with an handheld device– to discover learning objects satisfying their needs in a given environment.

Adaptive Computation Paradigm in Knowledge Representation

2009 ◽  
pp. 301-314
Author(s):  
Marina L. Gavrilova
Keyword(s):  
Knowledge Representation ◽  
Software Systems ◽  
New Paradigm ◽  
Information System Design ◽  
Adaptive Computation ◽  
Data Intensive ◽  
Collaborative Environment ◽  
Adaptive Models ◽  
E Learning ◽  
Computational Sciences

The constant demand for complex applications, the ever increasing complexity and size of software systems, and the inherently complicated nature of the information drive the needs for developing radically new approaches for information representation. This drive is leading to creation of new and exciting interdisciplinary fields that investigate convergence of software science and intelligence science, as well as computational sciences and their applications. This survey article discusses the new paradigm of the algorithmic models of intelligence, based on the adaptive hierarchical model of computation, and presents the algorithms and applications utilizing this paradigm in data-intensive, collaborative environment. Examples from the various areas include references to adaptive paradigm in biometric technologies, evolutionary computing, swarm intelligence, robotics, networks, e-learning, knowledge representation and information system design. Special topics related to adaptive models design and geometric computing are also included in the survey.

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