| 1. |
- Bunea, Ramona, et al.
(författare)
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Exploiting dynamic privacy in socially regularized recommenders
- 2012
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Ingår i: Data Mining Workshops (ICDMW), 2012 IEEE 12th International Conference on. - : IEEE. - 9780769549255 ; , s. 539-546
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Konferensbidrag (refereegranskat)abstract
- In this paper we introduce a privacy-aware collaborative filtering recommender framework which aims to address the privacy concern of profile owners in the context of social trust sparsity. While sparsity in social trust is mitigated by similarity driven trust using a probabilistic matrix factorization technique, the privacy issue is addressed by employing a dynamic privacy inference model. The privacy inference model exploits the underlying inter-entity trust information to obtain a personalized privacy view for each individual in the social network. We evaluate the proposed framework by employing an off-the-shelf collaborative filtering recommender method to make predictions using this personalized view. Experimental results show that our method offers better performance than similar non-privacy aware approaches, while at the same time meeting user privacy concerns.
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| 2. |
- Cena, Federica, et al.
(författare)
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Forging Trust and Privacy with User Modeling Frameworks : An Ontological Analysis
- 2011
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Ingår i: The First International Conference on Social Eco-Informatics. - : IARIA. - 9781612081632 ; , s. 43-48
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Konferensbidrag (refereegranskat)abstract
- With the ever increasing importance of social net- working sites and services, socially intelligent agents who are responsible for gathering, managing and maintaining knowledge surrounding individual users are of increasing interest to both computing research communities as well as industries. For these agents to be able to fully capture and manage the knowledge about a user’s interaction with these social sites and services, a social user model needs to be introduced. A social user model is defined as a generic user model (model capable of capturing generic information related to a user), plus social dimensions of users (models capturing social aspects of user such as activities and social contexts). While existing models capture a proportion of such information, they fail to model and present ones of the most important dimensions of social connectivity: trust and privacy. To this end, in this paper, we introduce an ontological model of social user, composed by a generic user model component, which imports existing well-known user model structures, a social model, which contains social dimensions, and trust, reputation and privacy become the pivotal concepts gluing the whole ontological knowledge models together.
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| 3. |
- Dokoohaki, Nima, et al.
(författare)
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Achieving Optimal Privacy in Trust-Aware Social Recommender Systems
- 2010
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Ingår i: SOCIAL INFORMATICS. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 9783642165665 ; , s. 62-79
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Konferensbidrag (refereegranskat)abstract
- Collaborative filtering (CF) recommenders are subject to numerous shortcomings such as centralized processing, vulnerability to shilling attacks, and most important of all privacy. To overcome these obstacles, researchers proposed for utilization of interpersonal trust between users, to alleviate many of these crucial shortcomings. Till now, attention has been mainly paid to strong points about trust-aware recommenders such as alleviating profile sparsity or calculation cost efficiency, while least attention has been paid on investigating the notion of privacy surrounding the disclosure of individual ratings and most importantly protection of trust computation across social networks forming the backbone of these systems. To contribute to addressing problem of privacy in trust-aware recommenders, within this paper, first we introduce a framework for enabling privacy-preserving trust-aware recommendation generation. While trust mechanism aims at elevating recommenders accuracy, to preserve privacy, accuracy of the system needs to be decreased. Since within this context, privacy and accuracy are conflicting goals we show that a Pareto set can be found as an optimal setting for both privacy-preserving and trust-enabling mechanisms. We show that this Pareto set, when used as the configuration for measuring the accuracy of base collaborative filtering engine, yields an optimized tradeoff between conflicting goals of privacy and accuracy. We prove this concept along with applicability of our framework by experimenting with accuracy and privacy factors, and we show through experiment how such optimal set can be inferred.
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| 4. |
- Dokoohaki, Nima, et al.
(författare)
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An Adaptive Framework for Discovery andMining of User Profiles from Social Web-based Interest Communities
- 2013
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Ingår i: The Influence of Technology on Social Network Analysis and Mining. - Wien : Springer. - 9783709113455 ; , s. 497-519
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Bokkapitel (refereegranskat)abstract
- Abstract Within this paper we introduce an adaptive framework for semi- tofully-automatic discovery, acquisition and mining of topic style interest profilesfrom openly accessible social web communities. To do such, we build an adaptivetaxonomy search tree from target domain (domain towards which we are gatheringand processing profiles for), starting with generic concepts at root moving down tospecific-level instances at leaves, then we utilize one of proposed Quest schemesto read the concept labels from the tree and crawl the source social networkrepositories for profiles containing matching and related topics. Using machinelearning techniques, cached profiles are then mined in two consecutive steps,utilizing a clusterer and a classifier in order to assign and predict correct profilesto their corresponding clustered corpus, which are retrieved later on by an ontology-based recommender to suggest and recommend the community members with theitems of their similar interest. Focusing on increasingly important digital culturalheritage context, using a set of profiles acquired from an openly accessible socialnetwork, we test the accuracy and adaptivity of framework. We will show that a tradeoff between schemes proposed can lead to adaptive discovery of highly relevant profiles.
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| 5. |
- Dokoohaki, Nima, et al.
(författare)
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An Enterprise Social Recommendation System for Connecting Swedish Professionals
- 2014
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Ingår i: Proceedings - IEEE 38th Annual International Computers, Software and Applications Conference Workshops, COMPSACW 2014. - : IEEE Communications Society. - 9781479935789 ; , s. 234-239
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Konferensbidrag (refereegranskat)abstract
- Most cooperative businesses rely on some form of social networking system to facilitate user profiling and networking of their employees. To facilitate the discovery, matchmaking and networking among the co-workers across the enterprises social recommendation systems are often used. Off-the-shelf nature of these components often makes it hard for individuals to control their exposure as well as their preferences of whom to connect to. To this end, trust based recommenders have been amongst the most popular and demanding solutions due to their advantage of using social trust to generate more accurate suggestions for peers to connect to. They also allow individuals to control their exposure based on explicit trust levels. In this work we have proposed for an enterprise trust-based recommendation system with privacy controls. To generate accurate predictions, a local trust metric is defined between users based on correlations of user's profiled content such as blogging, articles wrote, comments, and likes along with profile information such as organization, region, interests or skills. Privacy metric is defined in such a way that users have full freedom either to hide their data from the recommender or customize their profiles to make them visible only to users with defined level of trustworthy.
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| 6. |
- Dokoohaki, Nima, et al.
(författare)
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Deliverable 2.2 -Report describing methods for dynamic user profile creation : EU FP7 Smartmuseum Scientific Deliverable
- 2009
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Rapport (populärvet., debatt m.m.)abstract
- SMARTMUSEUM (Cultural Heritage Knowledge Exchange Platform) is a Research and Development project sponsored under theEuropeans Commission’s 7th Framework. The overall objective of the project is to develop a platform for innovative servicesenhancing 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 ofinnovative multilingual services for increasing interaction between visitors and cultural heritage objects in a future smart museumenvironment, 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.
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| 7. |
- Dokoohaki, Nima
(författare)
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Deliverable D2.1 - Report of User Profile Formal Represen-tation and Metadata Keyword Extension : EU FP7 Smartmuseum project Scientific Deliverable
- 2008
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- SMARTMUSEUM (Cultural Heritage Knowledge Exchange Platform) is a Research and Development project sponsored under theEuropeans Commission’s 7th Framework. The overall objective of the project is to develop a platform for innovative servicesenhancing 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 ofinnovative multilingual services for increasing interaction between visitors and cultural heritage objects in a future smart museumenvironment, taking full benefit of digitized cultural information.The main objective of this deliverable is to deliver formalization for user profile format as well as giving an extension of keywordsused to describe the human side of access to cultural heritage.
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| 8. |
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| 9. |
- Dokoohaki, Nima, et al.
(författare)
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Mining divergent opinion trust networks through latent dirichlet allocation
- 2012
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Ingår i: 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. - : IEEE. - 9781467324977 ; , s. 879-886
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Konferensbidrag (refereegranskat)abstract
- While the focus of trust research has been mainly on defining and modeling various notions of social trust, less attention has been given to modeling opinion trust. When speaking of social trust mainly homophily (similarity) has been the most successful metric for learning trustworthy links, specially in social web applications such as collaborative filtering recommendation systems. While pure homophily such as Pearson coefficient correlation and its variations, have been favorable to finding taste distances between individuals based on their rated items, they are not necessarily useful in finding opinion distances between individuals discussing a trending topic, e. g. Arab spring. At the same time text mining techniques, such as vector-based techniques, are not capable of capturing important factors such as saliency or polarity which are possible with topical models for detecting, analyzing and suggesting aspects of people mentioning those tags or topics. Thus, in this paper we are proposing to model opinion distances using probabilistic information divergence as a metric for measuring the distances between people's opinion contributing to a discussion in a social network. To acquire feature sets from topics discussed in a discussion we use a very successful topic modeling technique, namely Latent Dirichlet Allocation (LDA). We use the distributions resulting to model topics for generating social networks of group and individual users. Using a Twitter dataset we show that learned graphs exhibit properties of real-world like networks.
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| 10. |
- Dokoohaki, Nima, et al.
(författare)
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Personalizing Human Interaction through Hybrid Ontological Profiling : Cultural Heritage Case Study
- 2008
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Ingår i: 1st Workshop on Semantic Web Applications and Human Aspects, (SWAHA08). ; , s. 133-140
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Konferensbidrag (refereegranskat)abstract
- In this paper we present a novel user profile formalization, which allows describingthe user attributes as well as history of user access for personalized, adaptive and interactiveexperience while we believe that our approach is applicable to different semantic applicationswe illustrate our solution in the context of online and onsite museums and exhibits visit. Weargue that a generic structure will allow incorporation of multiple dimensions of user attributesand characteristics as well as allowing different abstraction levels for profile formalization andpresentations. In order to construct such profile structures we extend and enrich existingmetadata vocabularies for cultural heritage to contain keywords pertaining to usage attributesand user related keywords. By extending metadata vocabularies we allow improvedmatchmaking between extended user profile contents and cultural heritage contents. Thisextension creates the possibility of further personalization of access to cultural heritageavailable through online and onsite digital libraries.
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