Matches in ScholarlyData for { ?s ?p ?o. }
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
- authorList hasItem item-2.
- authorList hasItem item-3.
- authorList hasLastItem item-3.
- item-1 type ListItem.
- item-1 hasContent remy-cazabet.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent leguistin-maud.
- item-2 next item-3.
- item-2 previous item-1.
- item-3 type ListItem.
- item-3 hasContent frederic-amblard.
- item-3 previous item-2.
- 5 creator maurice-van-keulen.
- 5 creator rolf-a-de-by.
- 5 creator victor-de-graaff.
- 5 type InProceedings.
- 5 label "Towards Geosocial Recommender Systems".
- 5 sameAs 5.
- 5 abstract "The usage of social networks sites (SNSs), such as Face- book, and geosocial networks (GSNs), such as Foursquare, has increased tremendously over the past years. The will- ingness of users to share their current locations and expe- riences facilitate the creation of geographical recommender systems based on user generated content (UGC). This idea has been used to create a substantial amount of geosocial recommender systems (GRSs), such as Gogobot, TripIt, and Trippy already, but can be applied to more complex scenar- ios, such as the recommendation of products with a strong binding to their region, such as real estate or vacation des- tinations. This extended form of GRS development requires advanced functionality for information collection (from the web, other social media and sensors), information enrichment (such as data quality assessment and advanced data analysis), and personalized recommendations. The creation of a toolset to cope with these challenges is the goal of this research project, for which the outline is presented in this paper.".
- 5 hasAuthorList authorList.
- 5 isPartOf proceedings.
- 5 keyword "Geoprofiles".
- 5 keyword "Geosocial networking".
- 5 keyword "Recommender systems".
- 5 keyword "User profiles".
- 5 title "Towards Geosocial Recommender Systems".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
- authorList hasItem item-2.
- authorList hasItem item-3.
- authorList hasLastItem item-3.
- item-1 type ListItem.
- item-1 hasContent victor-de-graaff.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent maurice-van-keulen.
- item-2 next item-3.
- item-2 previous item-1.
- item-3 type ListItem.
- item-3 hasContent rolf-a-de-by.
- item-3 previous item-2.
- 7 creator estevam-hruschka-junior.
- 7 creator saulo-pedro.
- 7 type InProceedings.
- 7 label "Collective Intelligence as a Source for Machine Learning Self-Supervision".
- 7 sameAs 7.
- 7 abstract "The recent growth of virtual communities, social web and information sharing gives to information retrieval and machine learning systems a source of information referred as the "wisdom of crowds". In this work we show that this information could be used not only as a source of knowledge but as a way to bring intelligent systems closer to users by using their opinion as part of the knowledge acquisition/validation allowing self-supervision. For that we have implemented a validation system for the NELL (Never-Ending Language Learner) system using the question answering platform given by the Yahoo!Answers web community. Moreover, we focus in this paper, in the validation of first order rules induced by NELL using its Rule Learning (RL) algorithm. This paper presents the main motivations for using a QA forum instead of other web-based validation sources; describes the proposed approach with a "Macro QA"-based component named SS-Crowd (self-supervisor agent based on the wisdom of crowds) and brings and discusses the obtained results and how they can impact in a never-ending learning system like NELL in which self-supervision plays a crucial role.".
- 7 hasAuthorList authorList.
- 7 isPartOf proceedings.
- 7 keyword "knowledge validation".
- 7 keyword "machine learning".
- 7 keyword "question answering".
- 7 keyword "self-supervision".
- 7 keyword "virtual communities".
- 7 title "Collective Intelligence as a Source for Machine Learning Self-Supervision".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
- authorList hasItem item-2.
- authorList hasLastItem item-2.
- item-1 type ListItem.
- item-1 hasContent saulo-pedro.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent estevam-hruschka-junior.
- item-2 previous item-1.
- 8 creator andrei-ciortea.
- 8 creator laurent-vercouter.
- 8 creator yann-krupa.
- 8 type InProceedings.
- 8 label "Designing Privacy-Aware Social Networks: A Multi-Agent Approach".
- 8 sameAs 8.
- 8 abstract "People do not generally mind that some personal information is shared, but that it is shared in the wrong ways and with inappropriate others. We introduce a model for the automatic detection of incompatible relationships among agents in a virtual community. We define this model to the aim of adding to the PrivaCIAS framework a new layer that follows the theory of contextual integrity in more depth. We describe in detail the implementation of a proof of concept privacy-aware photo-sharing social network that we had developed for Android smartphones. The social network was built on the extended PrivaCIAS framework, and thus illustrates its applicability in helping users to preserve privacy.".
- 8 hasAuthorList authorList.
- 8 isPartOf proceedings.
- 8 keyword "contextual integrity".
- 8 keyword "multi-agent systems".
- 8 keyword "normative organizations".
- 8 keyword "privacy".
- 8 keyword "social networking".
- 8 title "Designing Privacy-Aware Social Networks: A Multi-Agent Approach".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
- authorList hasItem item-2.
- authorList hasItem item-3.
- authorList hasLastItem item-3.
- item-1 type ListItem.
- item-1 hasContent andrei-ciortea.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent yann-krupa.
- item-2 next item-3.
- item-2 previous item-1.
- item-3 type ListItem.