being social
DESCRIPTION
Presentation about research projects in Telefonica related to context-aware and personalized information access. It was given in the Industrial Track for SIGIR2010TRANSCRIPT
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Being Social: Research in Context-aware and Personalized
Information Access @ Telefonica
Xavier Amatriain (@xamat)J.M. Pujol (@solso)
Karen Church (@karenchurch)
#SIGIR2010Geneva, July '10
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But first...
About Telefonica and Telefonica R&D
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About 71,000 professionals
About 257,000 professionals
Staff
Services
Finances Rev: 4,273 M€EPS(1): 0.45 €
Integrated ICT solutions for all
customers
Clients About 12 million
subscribers
About 260 million
customers
Basic telephone and data services
1989
SpainOperations in 25 countries
Geographies
Rev: 57,946 M€ EPS: 1.63 €
2000 2008
About 149,000 professionals
About 68 million
customers
Wireline and mobile voice, data and
Internet services
(1) EPS: Earnings per share
Rev: 28,485 M€EPS(1): 0.67 €
Operations in16 countries
Telefonica is a fast-growing Telecom
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Telco sector worldwide ranking by market cap (US$ bn)
Currently among the largest in the world
Source: Bloomberg, 06/12/09
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Telefonica R&D (TID)
MISSION“To contribute to the improvement of the Telefónica Group’s
competitivness through technological innovation”
n Founded in 1988
n Largest private R&D center in Spain
n More than 1100 professionals
n Five centers in Spain and two in Latin America
Telefónica was in 2008 the first Spanish company by R&D Investment and the third in the EU
Products / Services / Processes development
Technological Innovation (1)
R&D594 M€
4.384 M€
Applied research
R&D61 M€
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Scientific Research
Multimedia CoreMobile and Ubicomp
DATA MINING
User Modelling & Data Mining
HCIR
Content Distribution & P2P Wireless Systems
Social Networks
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Enough company talk already...
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Information Overload
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More is Less
Less Decisions
Worse Decisions
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Search engines don’t always hold the answer
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You are not alone!
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That's what friends are for...
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What's her name?
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Adriana
Catalan
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Porqpine
J.M. Pujol and P. Rodriguez
"Towards Distributed Social Search Engines", in WWW '09
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Standalone
Can
coex
ist
Lazy collaboration
Personalized
Contex
tawar
e
Distrib
utedCost effective
Privacypreserving
Socially aware
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WHAT IS PORQPINE? ● Distributed social web search engine● Locally caches the page & records user interactions
(e.g., bookmarking). ● Searches by querying local caches of a user’s
friends● Pages that friends have “interacted with” are ranked
higher
● It uses a proxy masking the identity of the friend
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Context Overload
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≠
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Mobile phones are “personal”
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Mobile users tend to seek “fresh” content
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Where is the nearest florist?
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Where is that really cool cocktail barI went to last month?
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What about discovery?
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What about information to help me decide?
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Interesting things close to me?
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Events near me?
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Can we improve the search and discovery experience of mobile
users by providing a readily available connection to their social
network?
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SSB (Social Search Browser)
K. Church et al. "SocialSearchBrowser: A novel mobile search and information discovery tool.", in IUI '10
K. Church et al. “The "Map Trap"? An evaluation of map versus text-based interfaces for location-based mobile search services”, in WWW '10
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SSBiPhone optimized web-application + Facebook app
When launched it centers on the users current physical location
Displays all queries/questions posted by other users in that location
As users pan/zoom the set of queries is updated
Users can post new queries or interact with queries of others
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Live Field Study in-the-wild
Apr 2009, 16 users, 1 week, ireland
Sept 2009, 34 users, 1 month, ireland
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A tool for helping and sharing…..
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A tool for supporting curiosity
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…..extension to my social network
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But ...
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Crowds are not always wise
● Predictions based on large datasets that are sparse and noisy
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User Feedback is Noisy
● What is the percentage of inconsistencies given an original rating
X. Amatriain et al. "I Like It, I Like It Not, Evaluating User Ratings Noise in Recommender Systems", UMAP '09
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Who Can we trust?
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“It is really only experts who can reliably account
for their reactions”
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The Wisdom of the Few
X. Amatriain et al. "The wisdom of the few: a collaborative filtering approach based on expert opinions from the web", SIGIR '09
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Expert-based CF
● expert = individual that we can trust to have produced thoughtful, consistent and reliable evaluations (ratings) of items in a given domain
● Expert-based Collaborative Filtering● Find neighbors from a reduced set of experts instead of
regular users.
1. Identify domain experts with reliable ratings
2. For each user, compute “expert neighbors”
3. Compute recommendations similar to standard kNN CF
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Working Prototypes
Music recommendations, mobile geo-located recommendations...
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Summary
➢ We all knew about information overload➢ But now there is also context overload
(especially on mobile)➢ One way to deal with both is to tap into the
social network➢ Many times friends can help but others you
need to move into the crowds➢ But crowds are not always wise➢ Sometimes you are better off with experts
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Thank you!@xamat