Recommendation systems are primarily used to predict the preference or rating of a user for an item. They are widely used in many commercial applications, including product and service recommendations, as well as content and friendship recommendations in social media. However, recommendation systems are not only used for products on Amazon or movies on Netflix but also locations. Location-based recommenders incorporate the location of users to provide relevant and precise recommendations. These can be a point of interest recommendations, such as restaurants, events in nearby locations, or posts and local trends in social media. In this chapter, we will cover different recommender systems, including collaborative filtering methods and location-based recommendation methods. We will take an example of a restaurant recommender system application...
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Table Of Contents
Geospatial Data Science Quick Start Guide
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Geospatial Data Science Quick Start Guide
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Overview of this book
Data scientists, who have access to vast data streams, are a bit myopic when it comes to intrinsic and extrinsic location-based data and are missing out on the intelligence it can provide to their models. This book demonstrates effective techniques for using the power of data science and geospatial intelligence to build effective, intelligent data models that make use of location-based data to give useful predictions and analyses.
This book begins with a quick overview of the fundamentals of location-based data and how techniques such as Exploratory Data Analysis can be applied to it. We then delve into spatial operations such as computing distances, areas, extents, centroids, buffer polygons, intersecting geometries, geocoding, and more, which adds additional context to location data. Moving ahead, you will learn how to quickly build and deploy a geo-fencing system using Python. Lastly, you will learn how to leverage geospatial analysis techniques in popular recommendation systems such as collaborative filtering and location-based recommendations, and more.
By the end of the book, you will be a rockstar when it comes to performing geospatial analysis with ease.
Table of Contents (9 chapters)
Preface
Free Chapter
Introducing Location Intelligence
Consuming Location Data Like a Data Scientist
Performing Spatial Operations Like a Pro
Making Sense of Humongous Location Datasets
Nudging Check-Ins with Geofences
Let's Build a Routing Engine
Getting Location Recommender Systems
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