Automatic Generation of MCQS from Domain Ontology- A Survey

2018 ◽  
Vol 06 (06) ◽  
pp. 99-102
Author(s):  
Sahana Serin V. P. ◽  
Viji Rajendran V.
Keyword(s):  
Automatic Generation ◽  
Domain Ontology

Two Ways for the Automatic Generation of Application Ontologies by Using BalkaNet

2020 ◽  
Vol 16 (2) ◽  
pp. 18-41
Author(s):  
Miljana Mladenović ◽  
Staša Vujičić Stanković ◽  
Vesna Pajić
Keyword(s):  
Automatic Generation ◽  
Domain Ontology ◽  
The Other ◽  
Preliminary Evaluation ◽  
Web Ontology Language ◽  
Class Hierarchy ◽  
Ontology Language ◽  
Rhetorical Figures

This article presents two methods for the automatic generation of application ontologies from the multilingual BalkaNet WordNets Web ontology language (OWL) representation. Both proposed methods are applied on the BalkaNet WordNets ontology for the Serbian language (SerWN). The first one uses only the SerWN, both for generating class hierarchy and instances of classes, while the other method combines the SerWN with a domain ontology. The first method was used to automatically generate the FoodOntology, whereas the second method to generate the ontology of rhetorical figures tropes. Preliminary evaluation results corroborate the soundness of the approach. Since BN consists of individual WNs for five Balkan languages and Czech, the methodology presented in this article can also be used for all these languages. The first method can also be used for other domains.

Requirements Elicitation by Defect Elimination

2012 ◽  
pp. 372-391
Author(s):  
G. S. Mahalakshmi ◽  
T. V. Geetha
Keyword(s):  
Automatic Generation ◽  
Domain Ontology ◽  
Software Requirements ◽  
Specific Information ◽  
Functional Requirements ◽  
Indian Logic ◽  
Problem Statement ◽  
Interactive Approach ◽  
Domain Specific ◽  
Defect Elimination

This paper aims to develop an Indian-logic based approach for automatic generation of software requirements from a domain-specific ontology. The structure of domain ontology is adapted from Indian logic. The interactive approach proposed in this paper parses the problem statement, and the section of domain ontology, which matches the problem statement, is identified. The software generates questions to stakeholders based on the identified concepts. The answer is analysed for presence of flaws or inconsistencies. Subsequent questions are recursively generated to repair the flaw in the previous answer. These answers are populated into requirements ontology, which contains problem specific information coupled with the interests of the stakeholder. The information gathered is stored in a database, which is later segregated into functional and non-functional requirements. These requirements are classified, validated and prioritized based on combined approach of AHP and stakeholders’defined priority. Conflict between requirements is resolved by the application of cosine correlation measure.

Video Ontology

2009 ◽  
pp. 1506-1511
Author(s):  
Jeongkyu Lee
Keyword(s):  
Language Processing ◽  
Building Blocks ◽  
Automatic Generation ◽  
Domain Ontology ◽  
Multimedia Data ◽  
Multimedia Content ◽  
Surveillance Systems ◽  
Low Level ◽  
Core Ontology ◽  
Feature Values

There has been a great deal of interest in the development of ontology to facilitate knowledge sharing and database integration. In general, ontology is a set of terms or vocabularies of interest in a particular information domain, and shows the relationships among them (Doerr, Hunter, & Lagoze, 2003). It includes machine-interpretable definitions of basic concepts in the domain. Ontology is very popular in the fields of natural language processing (NLP) and Web user interface (Web ontology). To take this advantage into multimedia content analysis, several studies have proposed ontology-based schemes (Hollink & Worring, 2005; Spyropoulos, Paliouras, Karkaletsis, Kosmopoulos, Pratikakis, Perantonis, & Gatos, 2005). Modular structure of the ontology methodology is used in a generic analysis scheme to semantically interpret and annotate multimedia content. This methodology consists of domain ontology, core ontology, and multimedia ontology. Domain ontology captures concepts in a particular type of domain, while core ontology is the key building blocks necessary to enable the scalable assimilation of information from diverse sources. Multimedia ontology is used to model multimedia data, such as audio, image, and video. In the multimedia data analysis the meaningful patterns and hidden knowledge are discovered from the database. There are existing tools for managing and searching the discovered patterns and knowledge. However, almost all of the approaches use low-level feature values instead of high-level perceptions, which make a huge gap between machine interpretation and human understanding. For example, if we have to retrieve anomaly from video surveillance systems, low-level feature values cannot represent such semantic meanings. In order to address the problem, the main focus of research has been on the construction and utilization of ontology for specific data domain in various applications. In this chapter, we first survey the state-of-the-art in multimedia ontology, specifically video ontology, and then investigate the methods of automatic generation of video ontology.

The Role of Visual Distractors in the Simon Effect

2017 ◽  
Vol 64 (6) ◽  
pp. 387-397 ◽  
Author(s):  
Luisa Lugli ◽  
Stefania D’Ascenzo ◽  
Roberto Nicoletti ◽  
Carlo Umiltà
Keyword(s):  
Simon Effect ◽  
Simon Task ◽  
Automatic Generation ◽  
Spatial Code ◽  
Attentional Model ◽  
Previous Evidence ◽  
Spatial Stimulus ◽  
Attentional Resources ◽  
Code Changes

Abstract. The Simon effect lies on the automatic generation of a stimulus spatial code, which, however, is not relevant for performing the task. Results typically show faster performance when stimulus and response locations correspond, rather than when they do not. Considering reaction time distributions, two types of Simon effect have been individuated, which are thought to depend on different mechanisms: visuomotor activation versus cognitive translation of spatial codes. The present study aimed to investigate whether the presence of a distractor, which affects the allocation of attentional resources and, thus, the time needed to generate the spatial code, changes the nature of the Simon effect. In four experiments, we manipulated the presence and the characteristics of the distractor. Findings extend previous evidence regarding the distinction between visuomotor activation and cognitive translation of spatial stimulus codes in a Simon task. They are discussed with reference to the attentional model of the Simon effect.

A Method for Reliability Assessment of Spatial Plate Structures Through Automatic Generation of Ultimate Collapse Modes

1991 ◽  
Vol 1991 (170) ◽  
pp. 483-491 ◽  
Author(s):  
Hiroo Okada ◽  
Yoshisada Murotsu ◽  
Keiji Ueyama ◽  
Minoru Harada ◽  
Kazuya Kondo
Keyword(s):  
Reliability Assessment ◽  
Automatic Generation ◽  
Plate Structures
Sign in / Sign up

Export Citation Format

Share Document