User interest expansion using spreading activation for generating recommendations

作者: Punam Bedi , Richa

DOI: 10.1109/ICACCI.2015.7275703

关键词:

摘要: In this paper, a novel user interest expansion approach for generating recommendations is proposed. The utilizes of as well semantic relatedness between the items along with context to generate recommendations. Ontologies are used represent domain knowledge. Spreading activation technique uses concepts in ontology expand which results generation diverse A prototype system has been designed and developed using various JAVA technologies Restaurant its performance evaluated precision, recall, F1 diversity metrics. Performance proposed Context Aware Recommender Systemwith Expansion (ECARS) compared System (CARS) Content Based (CB)

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