Application of Case Based Recommender System in the Tourism Sector for the Selection of Tourist Attraction Areas in Ethiopia
| dc.contributor.advisor | Bekele, Rahel (PhD) | |
| dc.contributor.author | Anteneh, Tamir | |
| dc.date.accessioned | 2021-04-09T05:55:46Z | |
| dc.date.accessioned | 2023-11-18T12:47:29Z | |
| dc.date.available | 2021-04-09T05:55:46Z | |
| dc.date.available | 2023-11-18T12:47:29Z | |
| dc.date.issued | 2014-06-06 | |
| dc.description.abstract | The aim of this research is to design a prototype case based recommender system for tourist attraction area and visiting time selection that can assist experts and tourists to make timely decisions. For the development of case based recommender system, essential knowledge was acquired through semi-structured interview and document analysis. Eight domain experts and fourteen visitors were interviewed to elicit the required knowledge about the selection process of attraction area. The acquired knowledge was modeled using hierarchical tree structure and it was represented using feature value case representation. At the end, jCOLIBRI programming tool was used to implement the system. The main data source (case base) used to develop case based recommender system for tourist attraction area selection is previous tourist cases collected from NTO and MoCT. As a retrieval algorithm, nearest neighbor retrieval algorithm is used to measure the similarity of new case (query) with cases in the case base. Accordingly, if there is a similarity between the new case and the existing case, the system assigns the solution (recommended attraction area and visiting time) of previous case as a solution to new case. To decide the applicability of the prototype system in the domain area, the system has been evaluated by involving domain experts and visitors through visual interaction using the criteria of easiness to use, time efficiency, applicability in the domain area and providing correct recommendation. Based on prototype user acceptance testing, the average performance of the system is 80% and 82% by domain experts and visitors respectively. The performance of the system is also measured using the standard measure of relevance (IR system) recall, precision and accuracy measures, where the system registers 83% recall, 61% precision and 85.4% accuracy. Finally, conclusion and future research directions are forwarded. | en_US |
| dc.identifier.uri | http://etd.aau.edu.et/handle/12345678/26029 | |
| dc.language.iso | en | en_US |
| dc.publisher | Addis Ababa University | en_US |
| dc.subject | Application | en_US |
| dc.subject | Case Based Recommender System | en_US |
| dc.subject | Tourism Sector | en_US |
| dc.subject | Selection | en_US |
| dc.subject | Tourist Attraction | en_US |
| dc.subject | Areas in Ethiopia | en_US |
| dc.title | Application of Case Based Recommender System in the Tourism Sector for the Selection of Tourist Attraction Areas in Ethiopia | en_US |
| dc.type | Thesis | en_US |