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Spatio-temporal recommendation in so...

Yin, Hongzhi.

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Spatio-temporal recommendation in social media

Record Type:	Electronic resources : Monograph/item
Title/Author:	Spatio-temporal recommendation in social media/ by Hongzhi Yin, Bin Cui.
Author:	Yin, Hongzhi.
other author:	Cui, Bin.
Published:	Singapore :Springer Singapore : : 2016.,
Description:	xiii, 114 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	1. Introduction -- 2. Temporal Context-Aware Recommendation -- 3. Spatial Context-Aware Recommendation -- 4. Location-based and Real-time Recommendation -- 5. Fast Online Recommendation.
Contained By:	Springer eBooks
Subject:	Recommender systems (Information filtering) -
Online resource:	http://dx.doi.org/10.1007/978-981-10-0748-4
ISBN:	9789811007484

Spatio-temporal recommendation in social media
Yin, Hongzhi.

Spatio-temporal recommendation in social media[electronic resource] /by Hongzhi Yin, Bin Cui. - Singapore :Springer Singapore :2016. - xiii, 114 p. :ill. (some col.), digital ;24 cm. - SpringerBriefs in computer science,2191-5768. - SpringerBriefs in computer science..

1. Introduction -- 2. Temporal Context-Aware Recommendation -- 3. Spatial Context-Aware Recommendation -- 4. Location-based and Real-time Recommendation -- 5. Fast Online Recommendation.

This book covers the major fundamentals of and the latest research on next-generation spatio-temporal recommendation systems in social media. It begins by describing the emerging characteristics of social media in the era of mobile internet, and explores the limitations to be found in current recommender techniques. The book subsequently presents a series of latent-class user models to simulate users' behaviors in decision-making processes, which effectively overcome the challenges arising from temporal dynamics of users' behaviors, user interest drift over geographical regions, data sparsity and cold start. Based on these well designed user models, the book develops effective multi-dimensional index structures such as Metric-Tree, and proposes efficient top-k retrieval algorithms to accelerate the process of online recommendation and support real-time recommendation. In addition, it offers methodologies and techniques for evaluating both the effectiveness and efficiency of spatio-temporal recommendation systems in social media. The book will appeal to a broad readership, from researchers and developers to undergraduate and graduate students.

ISBN: 9789811007484

Standard No.: 10.1007/978-981-10-0748-4doiSubjects--Topical Terms:

1002434
Recommender systems (Information filtering)

LC Class. No.: QA76.9.I58

Dewey Class. No.: 005.56

Spatio-temporal recommendation in social media
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100 1 $a Yin, Hongzhi. $3 2194856
245 1 0 $a Spatio-temporal recommendation in social media $h [electronic resource] / $c by Hongzhi Yin, Bin Cui.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2016.
300 $a xiii, 114 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a SpringerBriefs in computer science, $x 2191-5768
505 0 $a 1. Introduction -- 2. Temporal Context-Aware Recommendation -- 3. Spatial Context-Aware Recommendation -- 4. Location-based and Real-time Recommendation -- 5. Fast Online Recommendation.
520 $a This book covers the major fundamentals of and the latest research on next-generation spatio-temporal recommendation systems in social media. It begins by describing the emerging characteristics of social media in the era of mobile internet, and explores the limitations to be found in current recommender techniques. The book subsequently presents a series of latent-class user models to simulate users' behaviors in decision-making processes, which effectively overcome the challenges arising from temporal dynamics of users' behaviors, user interest drift over geographical regions, data sparsity and cold start. Based on these well designed user models, the book develops effective multi-dimensional index structures such as Metric-Tree, and proposes efficient top-k retrieval algorithms to accelerate the process of online recommendation and support real-time recommendation. In addition, it offers methodologies and techniques for evaluating both the effectiveness and efficiency of spatio-temporal recommendation systems in social media. The book will appeal to a broad readership, from researchers and developers to undergraduate and graduate students.
650 0 $a Recommender systems (Information filtering) $3 1002434
650 0 $a Social media. $3 786190
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650 2 4 $a Information Storage and Retrieval. $3 761906
650 2 4 $a Information Systems Applications (incl. Internet) $3 1565452
650 2 4 $a Database Management. $3 891010
700 1 $a Cui, Bin. $3 2194857
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a SpringerBriefs in computer science. $3 1567571
856 4 0 $u http://dx.doi.org/10.1007/978-981-10-0748-4
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