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{ "item_title" : "Point-Of-Interest Recommendation in Location-Based Social Networks", "item_author" : [" Shenglin Zhao", "Michael R. Lyu", "Irwin King "], "item_description" : "This book systematically introduces Point-of-interest (POI) recommendations in Location-based Social Networks (LBSNs). Starting with a review of the advances in this area, the book then analyzes user mobility in LBSNs from geographical and temporal perspectives. Further, it demonstrates how to build a state-of-the-art POI recommendation system by incorporating the user behavior analysis. Lastly, the book discusses future research directions in this area.This book is intended for professionals involved in POI recommendation and graduate students working on problems related to location-based services. It is assumed that readers have a basic knowledge of mathematics, as well as some background in recommendation systems.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/9/81/131/348/9811313482_b.jpg", "price_data" : { "retail_price" : "54.99", "online_price" : "54.99", "our_price" : "54.99", "club_price" : "54.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Point-Of-Interest Recommendation in Location-Based Social Networks|Shenglin Zhao

Point-Of-Interest Recommendation in Location-Based Social Networks

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Overview

This book systematically introduces Point-of-interest (POI) recommendations in Location-based Social Networks (LBSNs). Starting with a review of the advances in this area, the book then analyzes user mobility in LBSNs from geographical and temporal perspectives. Further, it demonstrates how to build a state-of-the-art POI recommendation system by incorporating the user behavior analysis. Lastly, the book discusses future research directions in this area.

This book is intended for professionals involved in POI recommendation and graduate students working on problems related to location-based services. It is assumed that readers have a basic knowledge of mathematics, as well as some background in recommendation systems.

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Details

  • ISBN-13: 9789811313486
  • ISBN-10: 9811313482
  • Publisher: Springer
  • Publish Date: July 2018
  • Dimensions: 9.21 x 6.14 x 0.23 inches
  • Shipping Weight: 0.37 pounds
  • Page Count: 101

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