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36
Ontology Guided Dynamic Preference Elicitation
"... A challenge for preference based recommender systems is to elicit user preferences in an accurate and efficient manner. Eliciting preferences from the user in the form of a query that is then used to filter items from a database can result in a coarse recommendation with numerous results returned. T ..."
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their preferences in a simple manner, through examples presented to them. The system then makes use of an ontology model, based on expert information and social web resources. It elicits the user’s preferences guided by this ontology in an interactive and dynamic manner. We show that this leads to more effective
EUMSSI: a Platform for Multimodal Analysis and Recommendation using UIMA
"... The EUMSSI project (Event Understanding through Multimodal Social Stream Interpretation) aims at developing technologies for aggregating data presented as unstructured information in sources of very different nature. The multimodal analytics will help organize, classify and clus-ter cross-media stre ..."
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The EUMSSI project (Event Understanding through Multimodal Social Stream Interpretation) aims at developing technologies for aggregating data presented as unstructured information in sources of very different nature. The multimodal analytics will help organize, classify and clus-ter cross-media
Interactive and Adaptable Media 289 Adaptive User Preference Modeling and Its Application to In-flight Entertainment
"... This paper first presents an adaptive user preference model for personalized service delivery systems. In this model, user preference is modeled by a two-layer tree with dynamic changeable structures. The top layer of the tree is used for modeling user’s long term service preference. Each node repre ..."
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is many, it is more efficient and easier to find the right preference items; (3) if the user desired service has been removed, the system can utilize the personalized hierarchy service structure of the preference tree to calculate and recommend similar services. After the introduction of the user
Recommender Systems and Social Networks: an application in Cultural Heritage
"... Abstract In the last decade Recommender Systems have become useful tools helping users to find "what they need" from considerable amount of data. One of the more obvious applications of such systems in the Cultural Heritage domain is to assist users when visiting cultural environments (su ..."
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recommendation approach that combines several aspects of users -i.e. their preferences (usually in the shape of items' metadata) and interactions within a social community modeled using hypergraphs -together with items' multimedia features and context information within a general framework that can
LA-CTR: A Limited Attention Collaborative Topic Regression for Social Media
"... Probabilistic models can learn users ’ preferences from the history of their item adoptions on a social media site, and in turn, recommend new items to users based on learned preferences. However, current models ignore psychological factors that play an important role in shaping online social behavi ..."
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Probabilistic models can learn users ’ preferences from the history of their item adoptions on a social media site, and in turn, recommend new items to users based on learned preferences. However, current models ignore psychological factors that play an important role in shaping online social
LumiNet An Organic Interactive Illumination Network Diploma Thesis at the Media Computing Group
"... I hereby declare that I have created this work completely on my own and used no other sources or tools than the ones listed, and that I have marked any citations accordingly. Hiermit versichere ich, dass ich die vorliegende Arbeit selbständig verfasst und keine anderen als die angegebenen Quellen un ..."
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I hereby declare that I have created this work completely on my own and used no other sources or tools than the ones listed, and that I have marked any citations accordingly. Hiermit versichere ich, dass ich die vorliegende Arbeit selbständig verfasst und keine anderen als die angegebenen Quellen und Hilfsmittel benutzt sowie Zitate kenntlich gemacht habe.
Recommending TV Programs: How far can we get at zero user effort?
, 1998
"... RECOMMENDATION REQUIRES EFFORT Collaborative filtering methods have been applied to a number of domains like books, videos, audio CDs and Usenet news. These systems require some effort on the part of users before they can generate recommendations (see for example [5] on the cold-start problem). Ho ..."
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Cited by 2 (0 self)
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). How much effort they require depends on domain and application. Some recommender systems for books or videos require rating a specific number of items before they generate the first prediction. If users can save money by not buying the wrong books and videos this effort might pay off. The Usenet news
Preface
, 2014
"... With the increasing availability of data, it becomes more important to have automatic methods to manage data and retrieve information. Data processing, especially in the era of Social Media, is changing users behaviours. Users are ever more interested in information rather than in mere raw data. Con ..."
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With the increasing availability of data, it becomes more important to have automatic methods to manage data and retrieve information. Data processing, especially in the era of Social Media, is changing users behaviours. Users are ever more interested in information rather than in mere raw data
unknown title
"... IOS Press Utilization of intelligent agents for supporting citizens in their access to e-government services 1 ..."
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IOS Press Utilization of intelligent agents for supporting citizens in their access to e-government services 1
Interactive Cognition: Exploring the Potential of Electronic Quote/Commenting. In: B. Gorayska & J.L. Mey (Eds.) Cognitive Technology: In Search of a Humane Interface.
, 1995
"... Human cognition is not an island unto itself. As a species, we are not Leibnizian Monads independently engaging in clear, Cartesian thinking. Our minds interact. That's surely why our species has language. And that interactivity probably constrains both what and how we think. Although Wittgens ..."
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Cited by 5 (2 self)
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Wittgenstein's argument that there could be no "private language" --because language is based on rulefollowing and rules are shared social conventions --is probably overstated and refutable, for present purposes it is valid enough: Language is the main medium of interaction of our species
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