rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Recommender Systems for Location-based Social Networks
  name:
    name part: Symeonidis, Panagiotis.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Ntempos, Dimitrios.
    role:
      role term: author.
  name:
    name part: Manolopoulos, Yannis.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2014
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: V, 108 p. 41 illus., 33 illus. in color. online resource.
  abstract: Online social networks collect information from users' social contacts and their daily interactions (co-tagging of photos, co-rating of products etc.) to provide them with recommendations of new products or friends. Lately, technological progressions in mobile devices (i.e. smart phones) enabled the incorporation of geo-location data in the traditional web-based online social networks, bringing the new era of Social and Mobile Web. The goal of this book is to bring together important research in a new family of recommender systems aimed at serving Location-based Social Networks (LBSNs). The chapters introduce a wide variety of recent approaches, from the most basic to the state-of-the-art, for providing recommendations in LBSNs. The book is organized into three parts. Part 1 provides introductory material on recommender systems, online social networks and LBSNs. Part 2 presents a wide variety of recommendation algorithms, ranging from basic to cutting edge, as well as a comparison of the characteristics of these recommender systems. Part 3 provides a step-by-step case study on the technical aspects of deploying and evaluating a real-world LBSN, which provides location, activity and friend recommendations. The material covered in the book is intended for graduate students, teachers, researchers, and practitioners in the areas of web data mining, information retrieval, and machine learning.
  table of contents: Introduction -- Recommender Systems -- Online Social Networks -- Location-based Social Networks -- Framework -- Algorithms -- Comparison -- Real Geo-social Recommender Systems -- Conclusions.
  note: by Panagiotis Symeonidis, Dimitrios Ntempos, Yannis Manolopoulos.
  subject:
    topic: Computer science
  subject:
    topic: Data mining
  subject:
    topic: Artificial intelligence
  subject:
    topic: Computer Science
  subject:
    topic: Data Mining and Knowledge Discovery
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Information Systems Applications (incl. Internet)
  classification: QA76.9.D343
  classification: 006.312
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: SpringerBriefs in Electrical and Computer Engineering
  identifier: 9781493902866
  identifier: http://dx.doi.org/10.1007/978-1-4939-0286-6
  record info:
    record creation date: 140208
    record change date: 20140208092652.0
    record identifier: 978-1-4939-0286-6