smar museum Project FP7-216923 SMARTMUSEUM Cultural Heritage Knowledge Exchange Platform Deliverable d2.2 SMARTMUSEUM Report describing methods for dynamic user profile creation orkpackage WP2- Self adaptive user profile management Task T2.3-Developing theoretical solution for dynamic user profile creation and modification Version 1.00 Date March 11 2009 Classification Public Status Draft Abstract SMARTMUSEUM (Cultural Heritage Knowledge Exchange Platform) is a Research and Development project sponsored under the Europeans Commission,s 7th Framework. The overall objective of the project is to develop a platform for innovative services enhancing on-site personalized access to digital cultural heritage through adaptive and privacy preserving user profiling Using on- site knowledge databases, global digital libraries and visitors'experiential knowledge, the platform makes possible the creation of innovative multilingual services for increasing interaction between visitors and cultural heritage objects in a future smart museum environment, taking full benefit of digitized cultural information The main objective of this deliverable is to describe a theoretical framework for management of dynamic user profiles SmarTmuseuMConsortium(www.smartmuseum Authors Responsible Editors: KTH, ELlKO, TKK apprise H Heritage Malta Grant Agreement Number: FP7-216923 国如 Platform
Grant Agreement Number: FP7-216923 Acronym: SMARTMUSEUM Project title: Cultural Heritage Knowledge Exchange Platform Project FP7-216923 SMARTMUSEUM Cultural Heritage Knowledge Exchange Platform Deliverable D2.2 SMARTMUSEUM Report describing methods for dynamic user profile creation Workpackage WP2 – Self adaptive user profile management Task T2.3 - Developing theoretical solution for dynamic user profile creation and modification Version 1.00 Date March 11, 2009 Classification Public Status Draft Abstract SMARTMUSEUM (Cultural Heritage Knowledge Exchange Platform) is a Research and Development project sponsored under the Europeans Commission’s 7th Framework. The overall objective of the project is to develop a platform for innovative services enhancing on-site personalized access to digital cultural heritage through adaptive and privacy preserving user profiling. Using onsite knowledge databases, global digital libraries and visitors’ experiential knowledge, the platform makes possible the creation of innovative multilingual services for increasing interaction between visitors and cultural heritage objects in a future smart museum environment, taking full benefit of digitized cultural information. The main objective of this deliverable is to describe a theoretical framework for management of dynamic user profiles. Authors SMARTMUSEUM Consortium (www.smartmuseum.eu) Responsible Editors: KTH, ELIKO, TKK
smar museum Executive Summary The purpose of this deliverable D2. 2 is introducing a theoretical framework for dynamic user profile management and its related operations specifically creation and modification of user profiles Existing methods for user behaviour monitoring and formalisation are studied and a state of art in broader picture of contextualization and personalization is given, taken into account the domain of the project, cultural heritage domain Within the proposed framework, we introduce two approaches, mainly contributing mechanisms used for learning and building user profiles as well as mechanisms for enabler personalized recommendation and filtering on behalf of museum users. Our approaches take into account the adaptivity and dynamisms of user profiles, as suggested user profile qualities This enables us to measure how effective profiling framework works The introduced framework allowing us to create and learn dynamic user profiles for SMARTMUSUEM project. We have used the generic user profile structure introduced in D2. 1 for generating generic and dynamic user profile structures, while by utilizin collaborative filtering we learn and use profiled prefernces of users of the platform. As collaborative filtering techniques are the main foundation of the work being done, we introduce recommendation as a substantial part of the proposed framework apprise H Heritage Malta Grant Agreement Number: FP7-216923 国如 Platform
Grant Agreement Number: FP7-216923 Acronym: SMARTMUSEUM Project title: Cultural Heritage Knowledge Exchange Platform Executive Summary The purpose of this deliverable D2.2 is introducing a theoretical framework for dynamic user profile management and its related operations specifically creation and modification of user profiles. Existing methods for user behaviour monitoring and formalisation are studied and a state of art in broader picture of contextualization and personalization is given, taken into account the domain of the project, cultural heritage domain. Within the proposed framework, we introduce two approaches, mainly contributing mechanisms used for learning and building user profiles as well as mechanisms for enabling personalized recommendation and filtering on behalf of museum users. Our approaches take into account the adaptivity and dynamisms of user profiles, as suggested user profile qualities. This enables us to measure how effective profiling framework works. The introduced framework allowing us to create and learn dynamic user profiles for SMARTMUSUEM project. We have used the generic user profile structure introduced in D2.1 for generating generic and dynamic user profile structures, while by utilizing collaborative filtering we learn and use profiled prefernces of users of the platform. As collaborative filtering techniques are the main foundation of the work being done, we introduce recommendation as a substantial part of the proposed framework
smar museum Introduction SMARTMUSEUM Project Deliverable purpose, scope and context Background Introduction to personalization, user modelling and profiling Profiles presentation 5555667899 Personalization Recommendation and Contextualization in museum domain Overview of existing work on personalization in cultural heritage State-of-art approaches to user profile learning and construction 10 Conceptual Clustering Naive Bayes Bayesian Network 15 Neighbourhood based methods Self-Organizing Map Nearest Neighbour 17 Latent Semantic Indexing/ Analysis State-of-art on recommenders and recommendation techniques Collaborative filtering User-based Approaches Item-based Approaches Model-based App proaches Similarity Measures Content-based filtering Hybrid filtering amic Profile Operations Statistical Learning and Construction of User Profiles Modelling and Measuring User Preferences and Interests 22 Selecting and Combining Initial Profile Learning Techniques Association rule mining Frequent closed item set mining Simple Collaborative Filtering: Utilizing Statistical User Profiles Dataset for the initial modelling Recalculation and incremental learning of user's preference nput data format for algorithms Output data buffering for algorithm Analysis Extended Collaborative Filtering: Utilizing Semantics and Social Trust Extending Recommender Systems with Semantics: A User-Item Ontological Model..28 User ontology Item Ontology Enriching Recommendations using Distributed Social Trust apprise H Heritage Malta Grant Agreement Number: FP7-216923 国如 Platform
Grant Agreement Number: FP7-216923 Acronym: SMARTMUSEUM Project title: Cultural Heritage Knowledge Exchange Platform Introduction ................................................................................................................................ 5 SMARTMUSEUM Project .................................................................................................... 5 Deliverable purpose, scope and context................................................................................. 5 Audience................................................................................................................................. 5 Background ................................................................................................................................ 6 Introduction to personalization, user modelling and profiling............................................... 6 Profiles Presentation............................................................................................................... 7 Profiles Qualities.................................................................................................................... 8 Personalization, Recommendation and Contextualization in Museum Domain........................ 9 Overview of existing work on personalization in cultural heritage ....................................... 9 State-of-art approaches to user profile learning and construction........................................ 10 Data Mining...................................................................................................................... 11 Conceptual Clustering...................................................................................................... 12 Naive Bayes...................................................................................................................... 14 Bayesian Network ................................................................................................................15 Neighbourhood based methods........................................................................................ 16 Self-Organizing Map............................................................................................................16 Nearest Neighbour ...............................................................................................................17 Latent Semantic Indexing / Analysis ...................................................................................17 State-of-art on recommenders and recommendation techniques ......................................... 18 Collaborative filtering ...................................................................................................... 19 User-based Approaches........................................................................................................19 Item-based Approaches........................................................................................................19 Model-based Approaches.....................................................................................................19 Similarity Measures .............................................................................................................20 Content-based filtering..................................................................................................... 21 Hybrid filtering................................................................................................................. 21 Dynamic Profile Operations..................................................................................................... 22 Statistical Learning and Construction of User Profiles........................................................ 22 Modelling and Measuring User Preferences and Interests............................................... 22 Selecting and Combining Initial Profile Learning Techniques........................................ 23 Association rule mining .......................................................................................................23 Frequent closed item set mining ..........................................................................................24 Simple Collaborative Filtering: Utilizing Statistical User Profiles.................................. 24 Dataset for the initial modelling...........................................................................................24 Recalculation and incremental learning of user's preference...............................................25 Input data format for algorithms..........................................................................................25 Output data buffering for algorithms ...................................................................................26 Analysis................................................................................................................................26 Extended Collaborative Filtering: Utilizing Semantics and Social Trust ........................ 28 Extending Recommender Systems with Semantics: A User-Item Ontological Model........28 User Ontology .................................................................................................................28 Item Ontology..................................................................................................................29 Enriching Recommendations using Distributed Social Trust ..............................................30
smartmuseum ecommendation prediction process Rating a new item event Generating a New Recommendation Event Extending Recommender Systems with Socio-Semantic Trust: An Evaluation Conclusion General Conclusions Detailed Conclusions: Selection of Algorithms and mechanisms Works Cited apprise H Heritage Malta Grant Agreement Number: FP7-216923 国如 Platform
Grant Agreement Number: FP7-216923 Acronym: SMARTMUSEUM Project title: Cultural Heritage Knowledge Exchange Platform Recommendation prediction process...............................................................................30 Rating a New Item Event ................................................................................................30 Generating a New Recommendation Event ....................................................................31 Extending Recommender Systems with Socio-Semantic Trust: An Evaluation .................32 Conclusion............................................................................................................................ 33 General Conclusions ........................................................................................................ 33 Detailed Conclusions: Selection of Algorithms and Mechanisms................................... 34 Works Cited.......................................................................................................................... 35
smar museum Introduction The purpose of this section is to introduce the SMARTMUSEUM Project Purpose, scope and context of this deliverable Intended audience for the deliverable SMARTMUSEUM Project SMARTMUSEUM(Cultural Heritage Knowledge Exchange Platform) is a Research and Development project sponsored under the Europeans Commissions 7th Framework. The overall objective of the project is to develop a platform for innovative services enhancing on- site personalised access to digital cultural heritage through adaptive and privacy preserving user profiling. Using on-site knowledge databases, global digital libraries and visitors experiential knowledge, the platform makes possible the creation of innovative multilingual services for increasing interaction between visitors and cultural heritage objects in a future smart museum environment taking full benefit of digitized cultural information The SMARTMUSEUM project supports achieving the following general goals Lowering costs of on-site access to digital cultural heritage content Improving structured, user behaviour and preference dependent on-site access to the vast repository of cultural heritage, Improving the individual and shared experiences people receive from cultural and scientific resources Bringing personalised cultural experience closer to non-expert communities Making real reuse of personal experiences related to cultural heritage access for a variety of interest groups Deliverable purpose, scope and context The purpose of this deliverable D2. 2 is to present: 1)A survey of existing approaches to dynamic user profile management and 2)A framework of implemented techniques for user profile management Audience The intended audience includes Primarily SMARTmUSEUM Partners involved in developing the user profile-related operations Project partners involved in SMARTMUSEUM WP2 apprise H Heritage Malta Grant Agreement Number: FP7-216923 国如 Platform
Grant Agreement Number: FP7-216923 Acronym: SMARTMUSEUM Project title: Cultural Heritage Knowledge Exchange Platform Introduction The purpose of this section is to introduce the: SMARTMUSEUM Project Purpose, scope and context of this deliverable Intended audience for the deliverable SMARTMUSEUM Project SMARTMUSEUM (Cultural Heritage Knowledge Exchange Platform) is a Research and Development project sponsored under the Europeans Commission‘s 7th Framework. The overall objective of the project is to develop a platform for innovative services enhancing onsite personalised access to digital cultural heritage through adaptive and privacy preserving user profiling. Using on-site knowledge databases, global digital libraries and visitors‘ experiential knowledge, the platform makes possible the creation of innovative multilingual services for increasing interaction between visitors and cultural heritage objects in a future smart museum environment, taking full benefit of digitized cultural information. The SMARTMUSEUM project supports achieving the following general goals: • Lowering costs of on-site access to digital cultural heritage content, • Improving structured, user behaviour and preference dependent on-site access to the vast repository of cultural heritage, • Improving the individual and shared experiences people receive from cultural and scientific resources, • Bringing personalised cultural experience closer to non-expert communities, • Making real reuse of personal experiences related to cultural heritage access for a variety of interest groups. Deliverable purpose, scope and context The purpose of this deliverable D2.2 is to present: 1) A survey of existing approaches to dynamic user profile management and 2) A framework of implemented techniques for user profile management. Audience The intended audience includes: Primarily SMARTMUSEUM Partners involved in developing the user profile-related operations Project partners involved in SMARTMUSEUM WP2