Hla Hla Moe

Work place: University of Technology (Yatanarpon Cyber City), Pyin Oo Lwin, Myanmar

E-mail: hla2moe@gmail.com

Website:

Research Interests: Applied computer science, Computational Science and Engineering, Software Construction, Software Development Process, Software Engineering, Theoretical Computer Science, Engineering

Biography

Hla Hla Moe: Research student for doctor degree for Information Technology in University of Technology (Yatanarpon Cyber City), major in Computer Science, Software Engineering. She received master degree in computer science from Computer University (Sittway). The field of her thesis is cross-domain recommendation for personalized semantic services. She is working as a teacher in Computer University (Sittway) and her research interested areas are web mining, semantic web and personalization.

Author Articles
Building Ontologies for Cross-domain Recommendation on Facial Skin Problem and Related Cosmetics

By Hla Hla Moe Win Thanda Aung

DOI: https://doi.org/10.5815/ijitcs.2014.06.05, Pub. Date: 8 May 2014

Nowadays, recommendation has become an everyday activity in the World Wide Web. An increasing amount of work has been published in various areas related to the recommender system. Cross-domain recommendation is an emerging research topic. This type of recommendations has barely been investigated because it is difficult to obtain public datasets with user preferences crossing different domains. To solve dataset problem, one of the solution is to create different domains. Ontology is playing increasingly important roles in many research areas such as semantics interoperability and knowledge base and creating domain. Ontology defines a common vocabulary and a shared understanding and is applied for real world applications. Ontology is a formal representation of a set of concepts within a domain and the relationships between those concepts. This paper presents an approach for building ontologies using Taxonomic conversational case-based reasoning (Taxonomic CCBR) to apply cross-domain recommendation based on facial skin problems and related cosmetics. For linking cross-domain recommendation, Ford-Fulkerson algorithm is used to build the bridge of the concepts between two domain ontologies (Problems domain as the source domain and Cosmetics domain as the target domain).

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