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2018 | OriginalPaper | Buchkapitel

A Comprehensive Context-Aware Recommender System Framework

verfasst von : Sergio Inzunza, Reyes Juárez-Ramírez

Erschienen in: Computer Science and Engineering—Theory and Applications

Verlag: Springer International Publishing

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Abstract

Context-Aware Recommender System research has realized that effective recommendations go beyond recommendation accuracy, thus research has paid more attention to human and context factors, as an opportunity to increase user satisfaction. Despite the strong tie between recommendation algorithms and the human and context data that feed them, both elements have been treated as separated research problems. This document introduces MoRe, a comprehensive software framework to build context-aware recommender systems. MoRe provides developers a set of state of the art recommendation algorithms for contextual and traditional recommendations covering the main recommendation techniques existing in the literature. MoRe also provides developers a generic data model structure that supports an extensive range of human, context and items factors that is designed and implemented following the object-oriented paradigm. MoRe saves developers the tasks of implementing recommendation algorithms, and creating a structure to support the information the system will require, proving concrete functionality, and at the same time is generic enough to allow developers adapt its features to fit specific project needs.

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Titel: A Comprehensive Context-Aware Recommender System Framework
verfasst von: Sergio Inzunza
Reyes Juárez-Ramírez
Verlag: Springer International Publishing
Buch: Computer Science and Engineering—Theory and Applications
Print ISBN: 978-3-319-74059-1

Electronic ISBN: 978-3-319-74060-7

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-74060-7_1

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