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Full-Text Articles in Physical Sciences and Mathematics
Distributed Local Trust Propagation Model And Its Cloud-Based Implementation, Dharan Kumar Reddy Althuru
Distributed Local Trust Propagation Model And Its Cloud-Based Implementation, Dharan Kumar Reddy Althuru
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World Wide Web has grown rapidly in the last two decades with user generated content and interactions. Trust plays an important role in providing personalized content recommendations and in improving our confidence in various online interactions. We review trust propagation models in the context of social networks, semantic web, and recommender systems. With an objective to make trust propagation models more flexible, we propose several extensions to the trust propagation models that can be implemented as configurable parameters in the system. We implement Local Partial Order Trust (LPOT) model that considers trust as well as distrust ratings and perform evaluation …
Mining Privacy Settings To Find Optimal Privacy-Utility Tradeoffs For Social Network Services, Shumin Guo
Mining Privacy Settings To Find Optimal Privacy-Utility Tradeoffs For Social Network Services, Shumin Guo
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Privacy has been a big concern for users of social network services (SNS). On recent criticism about privacy protection, most SNS now provide fine privacy controls, allowing users to set visibility levels for almost every profile item. However, this also creates a number of difficulties for users. First, SNS providers often set most items by default to the highest visibility to improve the utility of social network, which may conflict with users' intention. It is often formidable for a user to fine-tune tens of privacy settings towards the user desired settings. Second, tuning privacy settings involves an intricate tradeoff between …
Automatic Identification Of Interestingness In Biomedical Literature, Gaurish Anand
Automatic Identification Of Interestingness In Biomedical Literature, Gaurish Anand
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This thesis presents research on automatically identifying interestingness in a graph of semantic predications. Interestingness represents a subjective quality of information that represents its value in meeting a user's known or unknown retrieval needs. The perception of information as interesting requires a level of utility for the user as well as a balance between significant novelty and sufficient familiarity. It can also be influenced by additional factors such as unexpectedness or serendipity with recent experiences. The ability to identify interesting information facilitates the development of user-centered retrieval, especially in information semantic summarization and iterative, step-wise searching such as in discovery …
An Evolutionary Approximation To Contrastive Divergence In Convolutional Restricted Boltzmann Machines, Ryan R. Mccoppin
An Evolutionary Approximation To Contrastive Divergence In Convolutional Restricted Boltzmann Machines, Ryan R. Mccoppin
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Deep learning is an emerging area in machine learning that exploits multi-layered neural networks to extract invariant relationships from large data sets. Deep learning uses layers of non-linear transformations to represent data in abstract and discrete forms. Several different architectures have been developed over the past few years specifically to process images including the Convolutional Restricted Boltzmann Machine. The Boltzmann Machine is trained using contrastive divergence, a depth-first gradient based training algorithm. Gradient based training methods have no guarantee of reaching an optimal solution and tend to search a limited region of the solution space. In this thesis, we present …
What Machines Understand About Personality Words After Reading The News, Eric David Moyer
What Machines Understand About Personality Words After Reading The News, Eric David Moyer
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Vector-based lexical semantics is a powerful technique that still has many undiscovered applications. In this thesis I apply a vector-space lexical-semantic model newly developed by Mikolov et. al. trained on skip-grams to the lexical hypothesis in personality psychology. The method produces interpretable dimensions that are consistent across several sets of descriptive personality words. The dimensions include ones for conflict and positive and negative evaluation. However they are more descriptive of word usage semantics than of the characteristics of the thing described and thus do not include a recognizable component of the 5 factor model in their first 14 dimensions. They …