TY - GEN
T1 - Analysis of User Generated Content Based on a Recommender System and Augmented Reality
AU - González, Fernando
AU - Guzmán, Giovanni
AU - Torres-Ruiz, Miguel
AU - Sidorov, Grigori
AU - Mata-Rivera, Félix
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - Recommender systems have demonstrated to be very useful in various research areas such as education, e-government, e-commerce, and collaborative and entertainment applications. These systems are based on a set of preferences that aim to help users make decisions by offering different items or services that might interest them. However, by using traditional search approaches, the user often obtains results that do not match the desired interests. Thus, a new search approach is required to use semantic-based retrieval techniques to generate conceptually close results to user preferences. In this paper, a methodology to retrieve information about user preferences based on a recommender system and augmented reality is proposed. As a case study, an Android mobile application was implemented, considering augmented reality to recommend multiplex cinemas that are generated from the genres of movies preferred by users and their geographical location at the time of the search.
AB - Recommender systems have demonstrated to be very useful in various research areas such as education, e-government, e-commerce, and collaborative and entertainment applications. These systems are based on a set of preferences that aim to help users make decisions by offering different items or services that might interest them. However, by using traditional search approaches, the user often obtains results that do not match the desired interests. Thus, a new search approach is required to use semantic-based retrieval techniques to generate conceptually close results to user preferences. In this paper, a methodology to retrieve information about user preferences based on a recommender system and augmented reality is proposed. As a case study, an Android mobile application was implemented, considering augmented reality to recommend multiplex cinemas that are generated from the genres of movies preferred by users and their geographical location at the time of the search.
KW - Augmented reality applications
KW - Recommender system
KW - Semantic similarity computation
KW - Semantic-based retrieval
UR - http://www.scopus.com/inward/record.url?scp=85119853190&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-89586-0_17
DO - 10.1007/978-3-030-89586-0_17
M3 - Contribución a la conferencia
AN - SCOPUS:85119853190
SN - 9783030895853
T3 - Communications in Computer and Information Science
SP - 207
EP - 228
BT - Telematics and Computing - 10th International Congress, WITCOM 2021, Proceedings
A2 - Mata-Rivera, Miguel Félix
A2 - Zagal-Flores, Roberto
PB - Springer Science and Business Media Deutschland GmbH
T2 - 10th International Congress on Telematics and Computing, WITCOM 2021
Y2 - 8 November 2021 through 12 November 2021
ER -