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YOGAWORLD – V2.0 Ramya Balaji Dinesh Manoharan Malavika RupendraKumar

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Presentation on theme: "YOGAWORLD – V2.0 Ramya Balaji Dinesh Manoharan Malavika RupendraKumar"— Presentation transcript:

1 YOGAWORLD – V2.0 Ramya Balaji Dinesh Manoharan Malavika RupendraKumar
Pavithra Viswanathan

2 Introduction Yogaworld is a one-stop shop for Yoga enthusiasts
It includes poses for individuals in beginner to advanced levels Helps users find studios around them and browse through recommended poses based on their ailments Includes a mobile app featuring basic poses and a map to find studios

3 Objectives To provide a complete application for learning/knowing about yoga To provide a platform to purchase products related to yoga To make available information regarding health benefits of yoga and what poses to practice for specific disorders To enable easy access to information on a mobile platform

4 Functionalities Pose Search to select pose of choice
Studio Map to find nearest yoga studio Pose Recommendation based on health disorders Videos and step-by-step explanation of poses Mobile application containing basic pose videos

5 Competitor Analysis Poses Videos Social Media Map Merchandise
A2z yoga Yoga journal Artofliving /yoga yogawiz findyoga yogapoint YOGA WORLD Poses X Videos Social Media Map Merchandise Recommender System Cloud & App

6 Business Model Ad Revenue Studio Listings Amazon Product Sales
Google AdSense API can be integrated – advertising revenue Opening the site to Google’s Ad Display network Studio Listings Yoga Studios can be featured listings on site for a small fee Amazon Product Sales Directing product sales from site = revenue from Amazon

7 Architecture

8 Components Amazon EC2 Cloud APIs – Alchemy Google Maps Google Places
Google Geocoding Google Translate Amazon YouTube Flickr Sound cloud Bing Search Facebook – like, comment, share Twitter

9 App Components Pose finder Sends Query Result Search Query
Android Application architecture Web Service, JSON Pose finder Sends Query Result Search Query Database

10 Analytics Recommendation System Similarity Metrics
Item based Recommendation Similarity Metrics Log Likelihood Similarity Generic Item based Recommendation Accuracy: 0.83 Sample training Data Format: Pose type, Ailment Type, Body Part, Recommended Pose

11 Novelty Cloud Application Mobile App Recommender System SoLoMo
Amazon EC2 Cloud hosting Mobile App Incorporates basic video and maps functionalities Recommender System Pose Recommender System using Data Mining SoLoMo Social – Location – Mobile Fb-Google maps- Android

12 Team Contribution Member Contribution Ramya Balaji
Front-end, Google Maps, Places, Geocoding, Slides, YouTube, Novelty Dinesh Manoharan Front-end, Google Translate, Bing Search, fb, twitter, Flickr, EC2, Data Mining Malavika RupendraKumar Database Design, Amazon, Data Mining, EC2, Novelty Pavithra Viswanathan Database, Alchemy, Soundcloud, Data Mining, Android

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