Yahoo! Time Traveler
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Transcript of Yahoo! Time Traveler
Y! Time Traveler : Dissection Deepak Shevani Yahoo! Travel
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What is Yahoo! Time Traveler ?
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iOS mobile application
Your travel concierge
Creates travel itineraries
Version 1 launched for 29 cities – Featured 5 times in US AppStore
Version 2 launched for 70 cities – Faster, Smarter and Personal !!
What is Yahoo! Time Traveler ?
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1 2 3 Select your city Set start & end location Itinerary is ready
Lets see Time Traveler in action !
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How to built this ?
Data requirements
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› Points of interests within a city (POI) • Latitude, Longitude, Address, Opening Hours, Name, Category
› Time spent at POI • Average time that must be spent at this location
› Distances between POIs • Driving and Walking distances between locations
› Algorithm to compute the itinerary
Data requirements
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› Points of interests within a city (POI) • Latitude, Longitude, Address, Opening Hours, Name, Category • Use Yahoo! Travel APIs to gather information about POIs
› Time spent at POI • Average time that must be spent at this location • Use Flickr photos to determine average time spent at POIs
› Distances between POIs • Driving and Walking distances between locations • Use Yahoo! Geo APIs to compute these distances
› Algorithm to compute the itinerary
Design and Architecture
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Itinerary Generation is done in two phases
From PHASE 1
Phase 1 : Computing time spent at POI
Yahoo! Maps
Flickr Data Yahoo! Travel
User Streams POI Data
Generate POI Graph for city
Phase 2 : Generate path between POIs
Start Location End Location Time Constraint
Compute most profitable Path
POI Graph
Phase 1 – Flickr Data Mining § Steps to compute time spent at POIs within a city
› Extract all geo-tagged Flickr images for a given POI › Process the images ordered by click-time and author › Deduce the time spent by the users at POIs using first & last timestamps › Compute the mean of time spent by various users at a POI
§ Use Yahoo! Geo APIs travel time between POIs § Output : Weighted POI Graph for city
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Phase 2 – Path Computation § Orienteering Problem
› Given an edge weighted graph G=(V,E,w), and a pair of nodes ‘s’ & ‘t’ - find s-t walk of length at most ‘B’ and that maximizes some function ‘f’ on set of nodes in the path • Here ‘V’ is vertex set, ‘E’ is Edge set, ‘w’ is weight function, ‘B’ is path budget, ‘f’ is reward
function
§ Reducing our problem to Orienteering Problem • Each node in city graph is a POI, with cost = time spent, and price = popularity • Each edge in city graph has weight = travel time between POIs • ‘B’ denotes the maximum number of POIs allowed in a path • Reward Function ‘f’ is proportional to Flickr Users for a POI & its popularity
§ Results • The algorithm computes path between POIs at run time, in less than 2-3 seconds ( |V| < 30 )
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References § Chandra Chekuri, Martin Pal. A Recursive Greedy Algorithm foe
Walks in Directed Graphs, IEEE Symposium 2005 § Munmun De Chaudhary. DeConstructing Travel Itineraries from
tagged Geo Temporal Breadcrumbs WWW2010 § Yahoo Geo Technologies http://developer.yahoo.com/geo/geoplanet/ § Flickr APIs http://www.flickr.com/services/api/ § Yahoo! Travel http://travel.yahoo.com
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