A Relational Recommender System Based on Domain Ontology

2011 ◽  
Author(s):  
Hikmet Kapusuzoglu ◽  
Sule Gunduz Öguducu
Keyword(s):  
Recommender System ◽  
Domain Ontology

Ontology-Based Context Modeling for Mobile Catering Recommendation

2013 ◽  
Vol 662 ◽  
pp. 953-956
Author(s):  
Dan Xiang Ai ◽  
Hui Zuo ◽  
Jun Yang
Keyword(s):  
Recommender System ◽  
Layer Structure ◽  
Domain Ontology ◽  
Use Case ◽  
Context Aware ◽  
Context Modeling ◽  
Specific Context ◽  
Contextual Model ◽  
Ontology Model ◽  
Upper Ontology

To support context-aware mobile recommendation, an ontology-based context modeling approach was proposed. We analyzed the framework of the mobile recommender system based on contextual model and suggested designing the model with two-layer structure including an upper ontology layer and a domain ontology layer. The ontologies provides formalizations representing the main entities, including users, objects, contexts, and their interactive relationships in mobile recommendation environments. A specific context ontology model for catering recommendation was developed and a use case of the instantiated context ontology was demonstrated.

Intelligent Petrol Station Recommender Based on Context Ontology and Rule Inference

2013 ◽  
Vol 303-306 ◽  
pp. 1412-1415
Author(s):  
Hui Zuo ◽  
Dan Xiang Ai ◽  
Jun Yang
Keyword(s):  
Recommender System ◽  
Domain Ontology ◽  
Petrol Station ◽  
Ontology Modeling ◽  
Ontology Model ◽  
Rule Inference ◽  
Upper Ontology

An intelligent mobile petrol station recommender system based on context ontology and rule inference is deigned. The approach of context ontology modeling specific for mobile recommendation is discussed. And a two-level context ontology model including upper ontology and domain ontology used in petrol station recommender is developed. The generation of recommendation rules based on the context ontologies and the process of the rule inference for recommendation are also demonstrated.

Evaluating the Construction of Domain Ontologies for Recommender Systems Based on Texts

2011 ◽  
pp. 145-158
Author(s):  
Stanley Loh ◽  
Daniel Lichtnow ◽  
Thyago Borges ◽  
Gustavo Piltcher
Keyword(s):  
Text Mining ◽  
Supervised Learning ◽  
Recommender Systems ◽  
Digital Library ◽  
Recommender System ◽  
Software Tools ◽  
Domain Ontology ◽  
Engineering Process ◽  
Electronic Documents ◽  
Domain Experts

This chapter investigates different aspects in the construction of a domain ontology to a content-based recommender system. The recommender systems suggests textual electronic documents from a Digital Library, based on documents read by the users and based on textual messages posted in electronic discussions through a web chat. The domain ontology is used to represent the user’s interest and the content of the documents. In this context, the ontology is composed by a hierarchy of concepts and keywords. Each concept has a vector of keywords with weights associated. Keywords are used to identify the content of the texts (documents and messages), through the application of text mining techniques. The chapter discusses different approaches for constructing the domain ontology, including the use of text mining software tools for supervised learning, the interference of domain experts in the engineering process and the use of a normalization step.

An Improved Hybrid Recommender System Using Multi-Based Clustering Method

2009 ◽  
Vol 129 (1) ◽  
pp. 125-132 ◽  
Author(s):  
Sutheera Puntheeranurak ◽  
Hidekazu Tsuji
Keyword(s):  
Recommender System ◽  
Clustering Method ◽  
Hybrid Recommender System ◽  
Hybrid Recommender

A behavior-based recommender system of university students' daily diets

2014 ◽  
Author(s):  
Kewen Tang ◽  
Wan Yi ◽  
Qin Yin ◽  
Zhaoxing Li
Keyword(s):  
University Students ◽  
Recommender System ◽  
Behavior Based
Sign in / Sign up

Export Citation Format

Share Document