Using a Rich Context Model for People-to-People Recommendation

Autor:	Marcelo Milrad, Alisa Sotsenko, Marc Jansen
Rok vydání:	2015
Předmět:	User information Context model Matching (statistics) Information retrieval Social network business.industry Computer science Process (engineering) media_common.quotation_subject Context (language use) Data type World Wide Web Quality (business) business media_common
Zdroj:	FiCloud
DOI:	10.1109/ficloud.2015.68
Popis:	In this paper we present an approach for People-to-People recommendations based on a Rich Context Model (RCM). We consider personal user information as contextual information used for our recommendations. The evaluation of our recommendation approach was performed on a social network of students. The obtained results do show a significant increase in performance while, at the same time, a slight increase in quality in comparison to a manual matching process. The proposed approach is flexible enough to handle different data types of contextual information and easy adaptable to other recommendation domains
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7387833ea569897e2af55163a88d4901 https://doi.org/10.1109/ficloud.2015.68 Zobrazit plný text záznamu