Noah  Rowe

Noah Rowe

1598235900

Recommending Restaurants With Asia Miles

This post discusses a case study of the possibilities of image and text feature extraction and how they can be used to enhance recommendation systems. We will also discuss how a Sesame Street character can help you decide where to eat, and how images are worth 2048 words and not 1000 as people might tell you.

Overview

Asia Miles has partnered with hundreds of restaurants to give our members the possibility of earning miles while eating at their favourite restaurants. The choice of restaurants in Hong Kong alone is mind boggling, so, how do we make sure our members receive relevant and exciting suggestions? Here is where data science comes in.

  • knowledge based: your basic filter on a search bar. e.g. “I want Japanese restaurants”
  • content based: the recommendation is based on the item and its features. We are basically recommending cafés because you once went to a café.
  • collaborative filtering: we recommend based on your behaviour and other people’s behaviour. Here, we have the “Other people liked…” section of recommenders.

Most recommendation engines are a mixture of these techniques, which means that we need some content information about the items that we want to recommend.

This leads us to our first challenge and the main topic of this post: “How do we extract information about restaurants?” There are plenty of sites that will provide a detailed taxonomy of a restaurant: cuisine, price range, atmosphere, location, opening hours, etc. However, this data is not usually available publicly, and it relies upon manual classification. We could have an army of summer interns eating and classifying the hundreds of restaurants in Hong Kong, but the classification would be limited and there is quite a sizeable number of “Japanese mid-range restaurants in Hong Kong”, for example.

#similarity #recommendations #data-science #nlp #image-processing #data science

What is GEEK

Buddha Community

Recommending Restaurants With Asia Miles
Ortez Infotech

Ortez Infotech

1619070154

Restaurant Management Software | Restaurant POS System

Simplified restaurant operations with solutions to manage KOT. Quick and efficient restaurant billing with the touch of your fingers. Get it now!

Keep in touch with us👇
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📲 91 94477 34981/ 91484 2428141

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What are the best restaurant mobile app design company?

Restaurant App Development Company is one in all the leading restaurant app development company that develop the most mobile solutions for your own restaurant business. we hold a full-scale development team that design and develop apps for Android and iOS platform. we’ve got worked with the several restaurant owners and startups globally to show their traditional offline business to an online approach.

Our Solutions for Restaurant Mobile App Design:

  • Food Ordering Portal
  • Food Ordering Mobile App
  • Restaurant Web Portal
  • Restaurant Mobile Apps
  • Food & Recipe Blog
  • Order Management Solutions
  • Inventory Management Solutions
  • Restaurant Search Portal
  • Food Delivery Marketplace

AppClues Infotech designs and develops a fully customizable and highly polished mobile app for your restaurant with back-end support as well, which allows restaurant owners to easily add/remove menu items, change the description and price of a menu item, add deals and offers, respond to customer’s reviews and messages, and send push notifications.

Our App Development Process:

  • Requirement Gathering
  • UI/UX Design
  • Prototype
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  • Quality Assurance
  • Deployment
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Our development team develops restaurant websites that are highly responsive and mobile-friendly. The websites are developed in a manner that displays the most view as per device hardware capabilities. we have also been engaged in the development of progressive websites that give you expertise like mobile apps. we reach for the stars and make the impossible not only possible but also profitable.

Have a Project in Mind? Let’s talk!!!

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Mobile Apps for Restaurants | How To Create a Restaurant App?

Developing a Restaurant app can become shortest way to get Restaurant success in little time. There are number of benefits by developing restaurant app. This blog walk you through the essential reason to develop mobile app for restaurant.

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Top-Notch Restaurant App Development Company in USA

AppClues Infotech is a well-known restaurant app development company in USA that designs, develops & markets online food ordering and restaurant mobile apps. Boost your restaurant startup with a mobile app solution from AppClues Infotech that offers amazing & creative restaurant app development services to clients around the world.

Contact us as soon as possible for the top-notch restaurant app development services.

**Why choose us for Restaurant App Development? **
• Online Ordering
• Supply Chain Management
• Push Notification
• 24/7 Maintenance & Support
• Multiple Platform Support
• Affordable service

For more info:
Website: https://www.appcluesinfotech.com/
Email: info@appcluesinfotech.com
Call: +1-978-309-9910

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Noah  Rowe

Noah Rowe

1598235900

Recommending Restaurants With Asia Miles

This post discusses a case study of the possibilities of image and text feature extraction and how they can be used to enhance recommendation systems. We will also discuss how a Sesame Street character can help you decide where to eat, and how images are worth 2048 words and not 1000 as people might tell you.

Overview

Asia Miles has partnered with hundreds of restaurants to give our members the possibility of earning miles while eating at their favourite restaurants. The choice of restaurants in Hong Kong alone is mind boggling, so, how do we make sure our members receive relevant and exciting suggestions? Here is where data science comes in.

  • knowledge based: your basic filter on a search bar. e.g. “I want Japanese restaurants”
  • content based: the recommendation is based on the item and its features. We are basically recommending cafés because you once went to a café.
  • collaborative filtering: we recommend based on your behaviour and other people’s behaviour. Here, we have the “Other people liked…” section of recommenders.

Most recommendation engines are a mixture of these techniques, which means that we need some content information about the items that we want to recommend.

This leads us to our first challenge and the main topic of this post: “How do we extract information about restaurants?” There are plenty of sites that will provide a detailed taxonomy of a restaurant: cuisine, price range, atmosphere, location, opening hours, etc. However, this data is not usually available publicly, and it relies upon manual classification. We could have an army of summer interns eating and classifying the hundreds of restaurants in Hong Kong, but the classification would be limited and there is quite a sizeable number of “Japanese mid-range restaurants in Hong Kong”, for example.

#similarity #recommendations #data-science #nlp #image-processing #data science