Development of a knowledge base using human experience semantic network for instructive texts

An organized knowledge base plays a vital role in retaining knowledge. Instructive text (iText) consists of a set of instructions to accomplish a task or operation. In the case of iText, storing only entities and their relationships is not enough for capturing knowledge from iTexts. iTexts consists of parameters and attributes of different entities and their actions based on different operations. The values differ for every operation or procedure for the same entity. As a result, existing approaches created limitations in capturing knowledge from iTexts. This research presents a knowledge base for capturing and retaining knowledge from iTexts existing in operational documents. From each iTexts, small pieces of knowledge are extracted and represented as nodes and edges in the form of a knowledge network called the human experience semantic network (HESN). The knowledge base also consists of domain knowledge having different classified terms and key phrases of the specific domain.

Name thesis:degree_name

Master of Applied Science (MASc)

Discipline thesis:degree_discipline

Applied Bioscience

Grantor

University of Ontario Institute of Technology

Year dc:date.issued

2021

Author dc:creator

• Jabar, Sk Sami Al

Advisor dc:contributor.advisor

• Gaber, Hossam

• Knowledge-base
• Natural language processing
• Human experience semantic network
• Entity relationship extraction
• Knowledge representation

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/10155/1408

OAI identifier oai:identifier

oai:ontariotechu.scholaris.ca:10155/1408