dc.contributor.author |
Jayasuriya, Subasinghe Mudiyanselage Prasdee Amanda |
|
dc.date.accessioned |
2021-07-18T11:18:41Z |
|
dc.date.available |
2021-07-18T11:18:41Z |
|
dc.date.issued |
2020 |
|
dc.identifier.citation |
Jayasuriya,Subsinghe Mudiyanselage Pradee Amanda (2020) “Transferly”: Knowledge Transfer system For New Employees Using Ontology, BEng. Dissertation Informatics Institute of Technology |
en_US |
dc.identifier.other |
2016179 |
|
dc.identifier.uri |
http://dlib.iit.ac.lk/xmlui/handle/123456789/594 |
|
dc.description.abstract |
Knowledge transfer is the process of passing valuable information and experience from one project or activity to another within or outside of an organization. After an employee joins a company, there is a requirement to perform a knowledge transferring process. The effect of knowledge management helps to improve the organizational performance, like the increase in the profit and human capital, improved productivity, more innovations of product and project or process-based results.
Knowledge control consists of knowledge codification and knowledge distributing specially to new users who join an organization. Learning about a new project involves a steep learning curve that takes time and resources. A well-developed knowledge model along with a Question and Answer system will help overcome this issue.
The proposed solution works as follows. The user will be asking a question from the Question and Answer System. Then the system will get the required details from the ontology and present it to the user. The user can also add data into the ontology using the above system.
Transferly follows a new approach to develop a Question and Answer system using semantic web by using Apache Jena by itself and getting information by manipulating the data. In addition, the ontology created for this project can be reused by anyone as it is a very simple ontology that covers a wide area of details about a project. |
en_US |
dc.title |
“Transferly”: Knowledge Transfer system For New Employees Using Ontology |
en_US |
dc.type |
Thesis |
en_US |