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Erschienen in:
Generation of Search Behavior by a Modification of Q-MDP Value Method Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

A Tag-Based Recommender System

verfasst von : Pietro De Caro, Maria Silvia Pini, Francesco Sambo

Erschienen in: Intelligent Autonomous Systems 13

Verlag: Springer International Publishing

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Abstract

Recommender systems are being used more and more on the web thanks to their ability to predict user preferences and drive user attention toward new items, increasing sales, and engagement. However, the use of such systems is still very limited to e-commerce and music or movies websites and, most of the times, the user is presented with recommendations limited to products. Our idea is to provide suggestions that are content-agnostic and that can be used to recommend mixed types of contents at the same time (for example, images, posts, and products). In such a way, the power of recommender systems can be exploited in very diverse contexts using a unique model with few adjustments. To achieve this, we provide a tag-based recommender system with a highly scalable implementation that is proposed with the aim of providing performance and reusability in a Software as a Service (SaaS) package.

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Vorheriges Kapitel Optimizing Support Vector Machine with Genetic Algorithm for Capacitive Sensing-Based Locomotion Mode Recognition
Nächstes Kapitel Clustering of Humanoid Robot Motions Executed in Response to Touch
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Metadaten
Titel
A Tag-Based Recommender System
verfasst von
Pietro De Caro
Maria Silvia Pini
Francesco Sambo
Copyright-Jahr
2016
Buch
Intelligent Autonomous Systems 13

Print ISBN: 978-3-319-08337-7

Electronic ISBN: 978-3-319-08338-4

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-08338-4_76

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