Being Social

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    26-Jan-2015

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Presentation about research projects in Telefonica related to context-aware and personalized information access. It was given in the Industrial Track for SIGIR2010

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<ul><li> 1. Being Social: Research in Context-aware and Personalized Information Access @ TelefonicaXavierAmatriain(@xamat) J.M.Pujol(@solso)KarenChurch(@karenchurch) #SIGIR2010Geneva,July'10 </li></ul> <p> 2. But first... About Telefonica and Telefonica R&amp;D 3. Telefonica is a fast-growing Telecom 1989 20002008 ClientsAbout 12About 68About 260 million million million subscribers customerscustomersServicesBasicWireline and mobileIntegrated ICT telephone and voice, data and solutions for alldata services Internet services customers GeographiesOperations inOperations in Spain 25 countries16 countries StaffAbout 71,000About 149,000 About 257,000professionalsprofessionals professionals Finances Rev: 4,273 M Rev: 28,485 MRev: 57,946 M EPS(1): 0.45 EPS(1): 0.67 EPS: 1.63 (1) EPS: Earnings per share 4. Currently among the largest in the worldTelco sector worldwide ranking by market cap (US$ bn) Source: Bloomberg, 06/12/09 5. Telefonica R&amp;D (TID) MISSIONTo contribute to the improvement of the n Founded in 1988Telefnica Groups n Largest private R&amp;D center in Spain competitivness through n More than 1100 professionals technological innovation n Five centers in Spain and two in Latin America Telefnica was in 2008 the first Spanish company by R&amp;D Investment and the third in the EUApplied R&amp;D research 61 M R&amp;D Products / Services / Processes594 M development4.384 M Technological Innovation (1) 6. Scientific Research Mobile and Ubicomp Multimedia CoreUser Modelling &amp;Data MiningHCIR DATA MININGWireless Systems Content Distribution &amp; P2P Social Networks 7. Enough company talk already... 8. Information Overload 9. More is LessW or seD ec isns ioionsisec Dses L 10. Search engines dont always hold the answer 11. You are not alone! 12. That'swhatfriendsarefor... 13. What's her name? 14. Catalan Adriana 15. Porqpine J.M. Pujol and P. Rodriguez "Towards Distributed Social Search Engines", in WWW '09 16. Soci e ar al lywPersonalized aawxt Starteon ane Cd al onLazycollaboration e d e Costeffectiveuttibis tr ex is oDc an PrivacypreservingC 17. WHAT IS PORQPINE? Distributed social web search engine Locally caches the page &amp; records user interactions (e.g., bookmarking). Searches by querying local caches of a users friends Pages that friends have interacted with are ranked higher It uses a proxy masking the identity of the friend 18. Context Overload 19. 20. Mobile phones are personal 21. Mobile users tend to seek fresh content 22. Where is the nearest florist? 23. Where is that really cool cocktail bar I went to last month? 24. What about discovery? 25. What about information to help me decide? 26. Interesting things close to me? 27. Events near me? 28. Can we improve the search and discovery experience of mobile users by providing a readily available connection to their socialnetwork? 29. 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 30. SSBiPhone optimized web-application + Facebook appWhen launched it centers on theusers current physical locationDisplays all queries/questionsposted by other users in thatlocationAs users pan/zoom the set ofqueries is updatedUsers can post new queries orinteract with queries of others 31. Apr 2009, 16 users, 1 week, ireland Live Field Study in-the-wildSept 2009, 34 users, 1 month, ireland 32. A tool for helping and sharing.. 33. A tool for supporting curiosity 34. ..extension to my social network 35. But ... 36. Crowds are not always wise Predictions based on large datasets that are sparse and noisy 37. User Feedback is Noisy X. Amatriain et al. "I Like It, I Like It Not, Evaluating User RatingsNoise in Recommender Systems", UMAP '09 Whatisthepercentageofinconsistenciesgivenan originalrating 38. Who Can we trust? 39. Itisreallyonlyexperts whocanreliablyaccountfortheirreactions 40. The Wisdom of the Few X. Amatriain et al. "The wisdom of the few: a collaborative filteringapproach based on expert opinions from the web", SIGIR '09 41. 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 ratings2. For each user, compute expert neighbors3. Compute recommendations similar to standard kNN CF 42. Working Prototypes Music recommendations, mobile geo-located recommendations... 43. 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 thesocial network Many times friends can help but others youneed to move into the crowds But crowds are not always wise Sometimes you are better off with experts 44. Thank you! @xamat </p>