Semantically enriched web services for the travel industry
ACM SIGMOD Record
Communications of the ACM - The Blogosphere
IEEE Transactions on Knowledge and Data Engineering
Information and Management
An intelligent fuzzy-based recommendation system for consumer electronic products
Expert Systems with Applications: An International Journal
Acquiring and Revising Preferences in a Critique-Based Mobile Recommender System
IEEE Intelligent Systems
Journal of Management Information Systems
Harmonise: A Step Toward an Interoperable E-Tourism Marketplace
International Journal of Electronic Commerce
samap: An user-oriented adaptive system for planning tourist visits
Expert Systems with Applications: An International Journal
Enhancing hotel search with semantic web technologies
Journal of Theoretical and Applied Electronic Commerce Research
Expert Systems with Applications: An International Journal
Building an expert travel agent as a software agent
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
An innovative mobile electronic tourist guide application
Personal and Ubiquitous Computing
Ontological recommendation multi-agent for Tainan City travel
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
SPETA: Social pervasive e-Tourism advisor
Telematics and Informatics
Expert Systems with Applications: An International Journal
SOLAR: Social Link Advanced Recommendation System
Future Generation Computer Systems
International Journal of Human Capital and Information Technology Professionals
SABUMO: Towards a collaborative and semantic framework for knowledge sharing
Expert Systems with Applications: An International Journal
PsyDis: Towards a diagnosis support system for psychological disorders
Expert Systems with Applications: An International Journal
PB-ADVISOR: A private banking multi-investment portfolio advisor
Information Sciences: an International Journal
Ant colony optimization for RDF chain queries for decision support
Expert Systems with Applications: An International Journal
Collective intelligence as mechanism of medical diagnosis: The iPixel approach
Expert Systems with Applications: An International Journal
GAT: Platform for automatic context-aware mobile services for m-tourism
Expert Systems with Applications: An International Journal
Creating a semantically-enhanced cloud services environment through ontology evolution
Future Generation Computer Systems
Ontology-based annotation and retrieval of services in the cloud
Knowledge-Based Systems
Hi-index | 12.06 |
The hotel industry is one of the leading stakeholders in the tourism sector. In order to reduce the traveler's cost of seeking accommodations, enforce the return ratio efficiency of guest rooms and enhance total operating performance, evaluating and selecting a suitable hotel location has become one of the most critical issues for the hotel industry. In this scenario, recommender services are increasingly emerging which employ intelligent agents and artificial intelligence to ''cut through'' unlimited information and obtain personalized solutions. Taking this assumption into account, this paper presents Sem-Fit, a semantic hotel recommendation expert system, based on the consumer's experience about recommendation provided by the system. Sem-Fit uses the consumer's experience point of view in order to apply fuzzy logic techniques to relating customer and hotel characteristics, represented by means of domain ontologies and affect grids. After receiving a recommendation, the customer provides a valuation about the recommendation generated by the system. Based on these valuations, the rules of the system are updated in order to adjust the new recommendations to past user experiences. To test the validity of Sem-Fit, the validation accomplished includes the interaction of the customer with the system and then the results are compared with the expert recommendation for each customer profile. Moreover, the values of precision and recall and F1 have been calculated, based on three points of view, to measure the degree of relevance of the recommendations of the fuzzy system, showing that the system recommendations are on the same level as an expert in the domain.