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Title: Semantic annotation in knowledge engineering, e-learning and computational linguistics
Author: Chan, Ching Lap
ISNI:       0000 0004 2741 1264
Awarding Body: City University
Current Institution: City, University of London
Date of Award: 2012
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In this work, a comprehensive study of semantic annotation has been carried out in early stage. The study focuses on the annotation requirements of human knowledge acquisition in knowledge engineering, e-Iearning and computational linguistics. Based on findings from the study, annotation of natural languages for linguistic analysis creates complicated data structures. Due to the complexity, almost all existing annotation schemes are designed to support only one application domain at one instance. Discovery of new knowledge by means of cross-domains text analysis is limited by the capability of these annotation schemes. To realize the findings in the study and provide solution to the problem, a new general-purpose annotation archival scheme has been developed but not limited to (1) Enable true cross-domain data analysis in knowledge engineering, e-Learning and computational linguistics, and (2) Organize complex structure of human knowledge annotation in an accessible manner, so they can be analyzed in multiple layers through retrieval, search, visualization and etc. To further verify the contributions of the new semantic annotation scheme in real application, experiments has been carried out in several areas, namely (1) collaborative retrieval of complex linguistic information, (2) computer-assisted production of learning material and (3) relevancy comparison between text. In (1), the annotation scheme is applied in a cloud-based platform for hosting parallel multilingual corpora leading to new applications such as computer assisted pattern visualization, speech analysis, speech-to-text transcription and statistical analysis. In (2), the annotation scheme provides support to applications that produce reader friendly learning material suites for teacher, and as a result improve learning quality. In (3), the annotation scheme provides support to a text' comparison platform that carries out writing assessment semantically. XIII
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available