AK Tourism: A Property Graph Ontology-based Tourism Recommender System

Recommender system (RS) is used to overcome the problem of information overload over the World Wide Web.Most of the time, users will be returned with a huge number of links when they do a Point of Interest (POI) search for interesting places to visit via the search engine. RS overcomes the pro...

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Main Authors: Keng, Seong She, Su, Cheng Haw, Yu, Gene Loh, Fang, Fang Chua
Format: Conference or Workshop Item
Language:English
Published: 2018
Subjects:
Online Access:https://repo.uum.edu.my/id/eprint/25195/1/KMICE%202018%2083%2088.pdf
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author Keng, Seong She
Su, Cheng Haw
Yu, Gene Loh
Fang, Fang Chua
author_facet Keng, Seong She
Su, Cheng Haw
Yu, Gene Loh
Fang, Fang Chua
author_sort Keng, Seong She
collection UUM
description Recommender system (RS) is used to overcome the problem of information overload over the World Wide Web.Most of the time, users will be returned with a huge number of links when they do a Point of Interest (POI) search for interesting places to visit via the search engine. RS overcomes the problem by analyzing automatically all the possible items information integrates with personalized user profiling (user preferences), and user rating. Specifically, ontology-based recommender system adopts new and alternative trends in recent years.Ontologies define rules to structure data, including interrelations between entities in the database.As such, it offers greater semantic relations within a particular domain. In this paper, we propose: (i) ontology representation, (ii) sample query in Cypher, and (iii) AK Tourism to demonstrate the recommender system in Malaysia tourism domain.
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spelling uum-251952018-11-21T01:57:33Z https://repo.uum.edu.my/id/eprint/25195/ AK Tourism: A Property Graph Ontology-based Tourism Recommender System Keng, Seong She Su, Cheng Haw Yu, Gene Loh Fang, Fang Chua HD28 Management. Industrial Management Recommender system (RS) is used to overcome the problem of information overload over the World Wide Web.Most of the time, users will be returned with a huge number of links when they do a Point of Interest (POI) search for interesting places to visit via the search engine. RS overcomes the problem by analyzing automatically all the possible items information integrates with personalized user profiling (user preferences), and user rating. Specifically, ontology-based recommender system adopts new and alternative trends in recent years.Ontologies define rules to structure data, including interrelations between entities in the database.As such, it offers greater semantic relations within a particular domain. In this paper, we propose: (i) ontology representation, (ii) sample query in Cypher, and (iii) AK Tourism to demonstrate the recommender system in Malaysia tourism domain. 2018-07-25 Conference or Workshop Item PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/25195/1/KMICE%202018%2083%2088.pdf Keng, Seong She and Su, Cheng Haw and Yu, Gene Loh and Fang, Fang Chua (2018) AK Tourism: A Property Graph Ontology-based Tourism Recommender System. In: Knowledge Management International Conference (KMICe) 2018, 25 –27 July 2018, Miri Sarawak, Malaysia. http://www.kmice.cms.net.my/ProcKMICe/KMICe2018/toc.html
spellingShingle HD28 Management. Industrial Management
Keng, Seong She
Su, Cheng Haw
Yu, Gene Loh
Fang, Fang Chua
AK Tourism: A Property Graph Ontology-based Tourism Recommender System
title AK Tourism: A Property Graph Ontology-based Tourism Recommender System
title_full AK Tourism: A Property Graph Ontology-based Tourism Recommender System
title_fullStr AK Tourism: A Property Graph Ontology-based Tourism Recommender System
title_full_unstemmed AK Tourism: A Property Graph Ontology-based Tourism Recommender System
title_short AK Tourism: A Property Graph Ontology-based Tourism Recommender System
title_sort ak tourism a property graph ontology based tourism recommender system
topic HD28 Management. Industrial Management
url https://repo.uum.edu.my/id/eprint/25195/1/KMICE%202018%2083%2088.pdf
work_keys_str_mv AT kengseongshe aktourismapropertygraphontologybasedtourismrecommendersystem
AT suchenghaw aktourismapropertygraphontologybasedtourismrecommendersystem
AT yugeneloh aktourismapropertygraphontologybasedtourismrecommendersystem
AT fangfangchua aktourismapropertygraphontologybasedtourismrecommendersystem