ΕΠΛ 435: Αλληλεπίδραση Ανθρώπου Υπολογιστή

1. ΕΠΛ 435:Αλληλεπίδραση Ανθρώπου Υπολογιστή User Modeling Adaptation Personalization Based on lectures given by Dr. VaniaDimitrova, University of Leeds, UK

2. Can Human-Computer interaction become personalised? Adding personalisation features in computer systems The Personalisation Buzz • We want information and servicesto be tailored to what we need, what we want, what best fits • our current state and purpose. • Personalised Human-Human interaction: • Route direction • Finding places to visit • Buying new car • Finding people to get in touch with • …… http://www.personalizationmall.com/

3. Broad Definition of Personalisation • “Whenever something is modified in its configuration or behaviour by information about the user, this is personalisation.”(Searby, 2003) • One size does not fit all! • delivering the right information • to the right person • at the right time • in the right way

4. Have you come across any personalisation functionality? Today • “Businesses are no longer asking if they should do personalisation it is simply a matter of when and how” (Larsen, 2000) • E-commerce (e.g. Amazon, eBay) • Search (e.g. Google, Yahoo, Altavista) • Desktops (Microsoft) • Mobile devices (e.g. Vodafone, Siemens) Key industries are adopting personalisation

5. Why Do We Need Personalisation? • Available information • Abundance • Heterogeneity • Noise • Constraints (bandwidth, time) • People • Capabilities and background • Task, goal, intentions • Context • Affective states

6. Two Types of Personalisation Adaptable (customisable) systems • U is able to modify aspects of S to suit his/her own preferences Adaptive systems • S modifies its own behavior at least partly independently of specifications by U Intermediate cases • S proposes possible adaptations, U decides which ones to accept

7. What are the main advantages of personalising google search? Are there any possible drawbacks? Knowledge Management & Personalisation • Bryan Horling & Robby Bryant, Google engineers Personalised search with Google http://www.youtube.com/watch?v=EKuG2M6R4VM

8. Will personalisation play a role in tomorrow’s technology? Technologies of Tomorrow • What will be the technologies in 2015? • And in 2020? http://www.ted.com/ • The Sixth Sense http://www.ted.com/talks/lang/eng/pattie_maes_demos_the_sixth_sense.html

9. Example: User-adaptable Interface Customise your web browser my.yahoo.com

10. Example: User-adaptive Interface Smart menus MS Windows

11. Example: Purchase Recommendations • Too much content • Too many choices

12. Example: Personalised Assistants Humanising the digital experience(http://www.soliloquy.com/solutions/notebook_demo.php) • Adaptive dialogue • Recognising user interests • Recommending relevant items

13. Example: Personalised Car Interface Receive the right service at the right time in the right way • Cognitive factors • Affective factors • User task, goal • Context awareness

14. How can the BBC news site be changed to become personalised? In class Exercise Question: Assume you use the BBC web page to read news. It behaves in the same way for every user.

15. Is Personalization the Holy Grail of Email Marketing? Deb Daufeldt is Founder & President of Second Story Solutions, LLC. Ezine@Articles, January 13, 2010 http://ezinearticles.com/?Is-Personalization-the-Holy-Grail-of-Email-Marketing?&id=3573208 How can personalisation be integrated in email systems and what is the added value? What is the connection between personalisation and taming the data? Knowledge Management and Personalisation User experience - Taming the Data Tiger

16. USER MODEL USER MODELAPPLICATION USER MODELACQUISITION INFORMATION ABOUT U ADAPTING TO U Schema of User-Adaptive Systems

17. Main Definitions • User Model – data structure that contains explicit assumptions on all aspects of U that are relevant to the adaptive behaviour of S • User Model Acquisition – procedure that incrementally construct the user model and whose functions are to: • storing, update, and delete entries in the user model; • maintain user model consistency; • ensure user model validity. • User Model Application – procedure that uses the user model to: • make predictions about U; • take decisions about how to adapt to U.

18. U’s MENU OPTIONS REASON ABOUTU’s OPTIONS REGISTERINGMENU SELECTION U’s MENU SELECTION DECIDE MENU CONTENT Example 1: Smart Menus

19. U’s PROFILEU’s KNOWLEDGE MODEL REASON ABOUTU’s KNOWLEDGE & PREFERENCES EXTRACTING INFO ABOUT U’s KNOWLEDGE AND PREFERENCES U’s BROWSING BEHAVIOUR U’s TEST PERFORMANCE GIVE HELP & FEEDBACKSUGGEST READING EXERCISES Example 2: User-adaptive Java Tutorial

20. Functions of User-adaptive Systems Supporting system use • Taking over parts of routine tasks(e.g. I-EMS – intelligent email sorting system) • Adapting the interface(e.g. Smart menus; adaptation for disable users) • Helping with system use(e.g. DiamondHelp – wizard helping with collaboration)

21. Functions of User-adaptive Systems (cont.) Supporting system use (cont.) • Mediating interaction with the real world(e.g. Lilsys – user’s availability for communication) • Controlling a dialogue(e.g. Kyoto City bus information system)

22. Functions of User-adaptive Systems (cont.) Supporting information acquisition • Helping users to find information(e.g. Google’s personalised search) • Recommending products(e.g. Amazon; Active Buyers Guide) • Tailoring information presentation(e.g. RIA – helping users search for real estates)

23. Functions of User-adaptive Systems (cont.) Supporting information acquisition (cont.) • Supporting collaboration(e.g. Agent Salon – finding people to connect with) • Supporting learning(e.g. SQL tutor – adaptive feedback)

24. Adaptivity & the Sixth Sense Technology Technologies of tomorrow: ubiquitous Example: The Sixth Sense http://www.ted.com/talks/lang/eng/pattie_maes_demos_the_sixth_sense.html What adaptive features can be added to the sixth sense technology? How will this be done? - Draw the architecture to show the main components.

25. Re(Design) Build an interactive version Evaluate Identify needs and establish requirements Who are the users? What differences matter? What adaptive features are required? Adaptivity & Interaction Design Identify criteria to judge the effectiveness of adaptivity - improved user satisfaction, increased sales, increased learning, efficiency, less errors, etc. Adaptive features often added features, how will this affect the existing design? Final Product Build high-fidelity prototypes to demonstrate adaptive features.

26. Recommender systems: intro • The problem: • too much content! • too many choices!

27. Recommendation Features

28. How do recommender systems work? Major types of algorithms • Collaborative or social filtering • Suggestion lists, “top-n” offers and promotions • Content-based recommenders • E-mail filters, clipping services • Hybrid recommenders • Suggestion lists, “top-n” offers and promotions

29. Collaborative filtering • Other’s ratings • What others like • My ratings • What I think like Give me what people similar to me would like “Word of mouth” “Voting”

30. Content-based Filtering • Content • Appropriate information about it • User profile • Relevant to the content User Profile Content Give me only those I like

31. Hybrid Filtering • Combining both • Building on advantages • Overcoming limitations User Profile Content

32. What do you think Amazon is using? Τμήμα Πληροφορικής

33. Καλό Βράδυ Τμήμα Πληροφορικής