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Authors: María del Carmen Rodríguez-Hernández 1 ; Sergio Ilarri 1 ; Raquel Trillo-Lado 1 and Francesco Guerra 2

Affiliations: 1 University of Zaragoza, Spain ; 2 University of Modena and Reggio Emilia, Italy

ISBN: 978-989-758-187-8

Keyword(s): Keyword-based Search, Recommendation Systems, Mobile Computing, Hidden Markov Model, Information Retrieval.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Databases and Information Systems Integration ; Enterprise Information Systems ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Non-Relational Databases ; Performance Evaluation and Benchmarking ; Query Languages and Query Processing ; Symbolic Systems ; User Profiling and Recommender Systems

Abstract: Due to the high availability of data, users are frequently overloaded with a huge amount of alternatives when they need to choose a particular item. This has motivated an increased interest in research on recommendation systems, which filter the options and provide users with suggestions about specific elements (e.g., movies, restaurants, hotels, books, etc.) that are estimated to be potentially relevant for the user. In this paper, we describe and evaluate two possible solutions to the problem of identification of the type of item (e.g., music, movie, book, etc.) that the user specifies in a pull-based recommendation (i.e., recommendation about certain types of items that are explicitly requested by the user). We evaluate two alternative solutions: one based on the use of the Hidden Markov Model and another one exploiting Information Retrieval techniques. Comparing both proposals experimentally, we can observe that the Hidden Markov Model performs generally better than the Informatio n Retrieval technique in our preliminary experimental setup. (More)

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Paper citation in several formats:
Rodríguez-Hernández, M.; Ilarri, S.; Trillo-Lado, R. and Guerra, F. (2016). Towards Keyword-based Pull Recommendation Systems.In Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-187-8, pages 207-214. DOI: 10.5220/0005865402070214

@conference{iceis16,
author={María del Carmen Rodríguez{-}Hernández. and Sergio Ilarri. and Raquel Trillo{-}Lado. and Francesco Guerra.},
title={Towards Keyword-based Pull Recommendation Systems},
booktitle={Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2016},
pages={207-214},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005865402070214},
isbn={978-989-758-187-8},
}

TY - CONF

JO - Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Towards Keyword-based Pull Recommendation Systems
SN - 978-989-758-187-8
AU - Rodríguez-Hernández, M.
AU - Ilarri, S.
AU - Trillo-Lado, R.
AU - Guerra, F.
PY - 2016
SP - 207
EP - 214
DO - 10.5220/0005865402070214

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