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Encyclopedia of Social Network Analysis and Mining pp 1–10Cite as

Spatiotemporal Personalized Recommendation of Social Media Content

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Synonyms

Location-based recommendation; Positional or layout effect in recommender systems; Spatiotemporal collaborative filtering; Time-sensitive recommendation

Glossary

Context:

The situation (which includes time, geographical location, location of a web page, etc.) in which recommendations are made to a user.

Feature:

Information (about a user, an item, and the context in which the item may be recommended to the user) that can be used to predict the response rate.

Graph:

A set of nodes connected by a set of edges.

Page:

A web page on which recommended items are placed.

Recommender:

A system that recommends items (e.g., news articles, blog posts) to users.

Response rate:

The probability that a user would respond positively to (e.g., click, share) a recommended item.

Definition

Social media sites (like twitter.com, digg.com, blogger.com) complement traditional media by incorporating content generated by regular people and allowing users to interact with content through sharing,...

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References

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Author information

Authors and Affiliations

  1. LinkedIn, Sunnyvale, CA, USA

    Bee-Chung Chen

Authors
  1. Bee-Chung Chen
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Corresponding author

Correspondence to Bee-Chung Chen .

Editor information

Editors and Affiliations

  1. Computer Science, University of Calgary, Calgary, Alberta, Canada

    Reda Alhajj

  2. University of Calgary Computer Science, Calgary, Canada

    Jon Rokne

Section Editor information

  1. Nanyang Technological University (NTU), Singapore, Singapore

    Gao Cong

  2. LinkedIn, Mountain View, CA, United States

    Bee-Chung Chen

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Chen, BC. (2017). Spatiotemporal Personalized Recommendation of Social Media Content. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7163-9_325-1

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  • DOI: https://doi.org/10.1007/978-1-4614-7163-9_325-1

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-7163-9

  • Online ISBN: 978-1-4614-7163-9

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

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