Presentation on theme: "Interoperability among user-adaptive systems in the World Wide Web Francesca Carmagnola Reading club 08 May 2007."— Presentation transcript:
Interoperability among user-adaptive systems in the World Wide Web Francesca Carmagnola email@example.com Reading club 08 May 2007
Master degree in Science and Communication (2004) Communication medium and techniques Currently Ph.D. at Department of Computer Science, University of Torino, Italy My research interests – Adaptive Hypermedia Systems – User Modeling – Semantic Web – Web 2.0 What about me?
Member of… SETA: Intelligent User Interface group (http://www.di.unito.it/~seta/).http://www.di.unito.it/~seta/ - Design and development of Intelligent Systems, based on distributed architectures, and exploiting Internet technologies -Exploitation of advanced AI techniques to improve the interaction with the users CIRC (Interdepartmental Centre of Research on Communication) at University of Turin Social Media Applications Research & Tagging Laboratory (http://www.smartlab.csp.it/) - Multimedia innovative solutions for mobile users and workers, by developing personalized services
The project which I am involved in…. Web 2.0 + Um adaptive mobile tourist guides DIADI E-tourism UbiquiTO-S iCITY Personalized Digital Television Interoperability among user-adaptive systems in the World Wide Web (Ph.D. research) Um + SW
User Modeling + Semantic Web User Modeling can benefit from techniques provided by SW: Standardization of languages Reuse of knowledge … Semantic Web can benefit from personalization since it enables sharing content and services which are tailored to the needs of individual users (reducing information overload, etc…)
DIADI (Project financed by Region Piemonte, Ministry of Economy, EU) Multi-channel adaptive platform, based on a semantic representation of contents, for the negotiation of requests toward providers Semantic representation of knowlegde (RDFS) Semantic representation of rules (inference rules and adaptation rules) SemanticSearchEngine (used to query the ontologies), implemented with SeRQL language over a RDF repository API delivered http://talea.csp.it/ithttp://talea.csp.it/it
UbiquiTO-S Project Prin/Cofin, financed by Miur, in collaboration with the universities of Udine, Pisa and with the CNR (Trento) General framework (modular architecture) to develop adaptive mobile tourist guides. In particular, the role of our research group is: - Study and management of the knowledge (concerning the user, the domain and the context) required in adaptive context-aware mobile guides (semantic modelling) - Module for the dynamic generation of user interface, on the basis of this knowledge.
Project for the development of a tourist context-aware guide which provides support and advices to the users considering the current interaction context. In particular, the role of our research group is: - Study of the meaning of the context in tourist context-aware guide (physique, social and personal context) - Ontological modelling of such a context E-Tourism (in collaboration with Telecom Italia lab)
Shift toward Web 2.0 Web 1.0Web 2.0 Centralized production of contents (top-down approach) Decentralized production of contents (bottom-up approach) Peer production Stand-alone userCommunity Social-network Predefined navigation pathsNavigation by tags
Web 2.0 + Adaptation Web 2.0Adaptation Decentralized production of contents (bottom-up approach) Peer production Recommendation of contents Adaptation to the device Community Social-network Recommendation of similar users (having similar interests) Navigation by tagsRecommendation of tags (most personal navigation)
Web 2.0 + Adaptation Adaptation can benefit from Web 2.0 user participation (insertion of information, tagging, annotations) to learn about the user and thus to create/improve her user model; Web 2.0 can benefit from adaptation exploitation of the user model in order to help the user in tagging and creating contents and to support the user in navigation; creation of communities of users through the combination of user modeling and participation (especially tagging); ….
iCITY (in collaboration with the Municipality of Torino and SMARTLAB - social media applications research and tagging Laboratory) Mobile; Adaptive; Web-based; Social guide; Providing personalized information about cultural events of the city of Torino
iCITY - Main functionalities navigate by categories - by tags access cultural events (by text and map ) Bookmarking preferred events access personalised recommendations Insert content: i)new event, ii)add information to events, iii) add comments Tagging event See and update his user model See users that inserted content Share bookmarks Share tags Share tags http://www.icity.di.unito.it/dsa/
Personalized Digital Television (in collaboration with Telecom Italia lab) Personalization techniques for the customization of the future television services Customization of the Electronic Program Guides (EPG) focused on the personalized selection of the TV programs to be advertised, on the basis of the user's interests. (Recommendations to help users on orientating into the very large information space available in Digital TV) Use of tagging to refine use model and navigation paths Exploitation of such techniques within a prototype system for the generation of personalized (EPGs). Multi-agent architecture to support the development of highly configurable hybrid recommender systems, which integrate different user modelling and recommendation techniques to improve the recommendations to the user.
FINALLY MY PERSONAL RESEARCH… Interoperability among user-adaptive systems in the World Wide Web (Ph.D. research)
Starting assumptions Personalization crucial in many areas (e-learning, tourism, digital libraries, e-commerce, etc.) The user spends her time interacting with many web-based adaptive systems Possibility of having common knowledge about the user shared across different systems Share knowledge about the user across the different systems she interact with!
Advantages of cross-systems personalization include in the user model features that one system could not acquire by itself (Carmagnola and Cena, 2006) increase the amount of information about users, since there is the chance to benefit from the efforts led by other modellers and systems. It lets the increased coverage since more aspects can be covered by the aggregated user model because of the variety of the contributing systems. Ums themselves can be more accurate and, as a consequence, the adaptation results are improved (quantitative and qualitative improvement) (Stewart, Celik et al. 2006), (Berkovsky 2005)
Advantages of cross-systems personalization speed up the phase of the user model inizialization (Kobsa, Koenemann et al. 2001) save the user from tedium of training new systems reduce the cost of user modelling sharing it among different applications and many others…
Challenges of cross-systems personalization Why should commercial competitive systems cooperate? How to preserve users privacy? How to cope with syntactic and semantic heterogeneity of information over the web? My research
More specifically… 2. Analysis of the phases required to get user model interoperability 3. Framework providing a common base for the interoperability of user model knowledge among user-adaptive systems in the World Wide Web 1.Analysis of the implications of interoperability in user modeling SyntacticSemantic
1. Analysis of the implications of interoperability in User Modeling How to ensure syntactic and semantic interoperability? Semantic Web techniques Languages for representing data ( RDF(S), OWL, etc…) Framework for stucturing data in a syntax-independent way (ontologies) Languages for reasoning over knowledge (SWRL, OWL-S) In my framework the User Model knowldege is ontologically represented (RDFS)
2. Analysis of the phases required to get user model interoperability The cooperation among systems to exchange user model knowledge can be seen as complex task: A Discovery phase: Finding out the systems which store knowledge on a same user * The most relevant researches have almost exclusively focused on the core part of the cooperation of user adaptive systems, that is the exchange of data about users B Exchange (*): Query for the required user data C Conflict resolution and evaluation: - Need for suitable stategies to cope with semantic interoperability - Need for suitable stategies to check and solve conflicts and evaluate if the exchanged data are reliable
3. Framework providing a common base for the interoperability of user model knowledge among user-adaptive systems in the World Wide Web Requirements: every user should be able to declare what information to make public every system should represent user knowledge in RDF(S) format and like pairs every system should make the repository (containing the semantic representation of the Um) available to other systems the available information should be updated systems must be able to access, in a simple and efficient way, to the user information which have been made available by other systems
Need for a framework for storing, querying and retrieving references to the semantic repositories: SESAME (http://openrdf.org/) - Open source Java framework that can be used as a database server which client applications can access through the HTTP protocol. -SeRQL to query repositories -To support Sesame servlet we encode the Java servlet technology in an Apache Tomcat environment.
What already done thus far…. A Discovery phase Identification algorithm, to discover systems which store knowledge on a same user 2 Java APIs to support designers and systems in performing such a task B Exchange Semantic representation of knowledge Semantic query for the required user data
What I would like to achieve from my visit in Leeds? C Conflict resolution and evaluation - Need for suitable strategies to cope with semantic interoperability (If system A says I like football and system B says I like soccer?) (If system A says I like football and system B says I like sport?) When semantic interoperability has been reached…. - Need for suitable strategies to check and solve conflicts and evaluate if the exchanged data are reliable (If system A says I like football and system B says I dont like soccer?) (If system A says I like football and volleyball, and system B says I dont like sports?) (If system A says I like football, and system B says I dont like football and system C says that I like football?)