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PUBLIC SENTIMENT VARIATIONS ANALYZING ON TWITTER

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Twitter has become a social site where millions of users can exchange their opinion. Sentiment analysis on Twitter data has provided an economical and effective way to expose public opinion timely, which is critical for decision making in various domains. In this work, we move one step further to interpret sentiment variations. We observed that […]

HARD AI PROBLEMS BASED CAPTCHA AS GRAPHICAL PASSWORDS SECURITY PRIMITIVE

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In this abstract, we introduce a new security primitive based on hard AI problems, namely, a novel family of graphical pass-word systems integrating Captcha technology, which we call CaRP (Captcha as gRaphical Passwords). CaRP is click-based graphical passwords, where a sequence of clicks on an image is used to derive a password. Unlike other click-based […]

TRACKING AND ANALYZING THE PUBLIC SENTIMENT VARIATIONS ON TWITTER

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In this abstract, we analyze public sentiment variations on Twitter and mine possible reasons behind such variations. To track public sentiment, we combine two state-of-the-art sentiment analysis tools to obtain sentiment information towards interested targets (e.g., “Obama”) in each tweet. Based on the sentiment label obtained for each tweet, we can track the public sentiment […]

CARP SCHEME FOR SECURITY PRIMITIVE BASED ON HARD AI PROBLEMS

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Using hard AI (Artificial Intelligence) problems for security is an exciting new paradigm. Under this paradigm, the most notable primitive invented is Captcha, which distinguishes human users from computers by presenting a challenge, i.e., a puzzle, beyond the capability of computers but easy for humans. Captcha is now a standard Internet security technique to protect […]

COOPERATIVE SPECTRUM SHARING BETWEEN ONE PRIMARY USER AND MULTIPLE SECONDARY USERS UNDER INCOMPLETE INFORMATION

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Contract theory is effective in designing incentive compatible mechanisms in a monopoly market under incomplete information, where the employer needs to sign a contract with employees before fully knowing their private information. The key idea is to offer the right contract items so that all agents have the incentive to truthfully reveal their private information. […]

AN EFFICIENT DATA ACCESS USING COOPERATIVE CACHING IN DISRUPTION TOLERANT NETWORKS

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Disruption tolerant networks (DTNs) consist of mobile devices that contact each other opportunistically. Most of current research efforts in DTNs focus on data forwarding, but only limited work has been done on providing efficient data access to mobile users. Our basic idea is to intentionally cache data at a set of network central locations (NCLs), […]

A NOVEL DATA ACCESS SCHEME IN DISRUPTION TOLERANT NETWORKS USING COOPERATIVE CACHING

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Our basic idea is to intentionally cache data at a set of network central locations (NCLs), which can be easily accessed by other nodes in the network. We develop an efficient approach to NCL selection in DTNs based on a probabilistic selection metric. The selected NCLs achieve high chances for prompt response to user queries […]

PAIRWISE CONSTRAINTS FOR ACCELERATED LEARNING-BASED INTERACTIVE IMAGE SEGMENTATION

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Image segmentation refers to the task of grouping image pixels into a meaningful partition such that pixels falling in the same group are similar to each other, and different than those in other groups, in terms of a perceptually meaningful similarity measure. Segmentation often is used as a pre-processing step before higher level image processing […]

A CONTRACT-BASED COOPERATIVE SPECTRUM SHARING MECHANISM

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Contract theory is effective in designing incentive compatible mechanisms in a monopoly market under incomplete information, where the employer needs to sign a contract with employees before fully knowing their private information. The key idea is to offer the right contract items so that all agents have the incentive to truthfully reveal their private information. […]

INTERACTIVE IMAGE SEGMENTATION BASED ON ACCELERATED LEARNING USING PAIRWISE CONSTRAINTS

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Segmentation often is used as a pre-processing step before higher level image processing or understanding. Manually segmenting images can be laborious and time-consuming, especially for large images, and can be prone to subjectivity. At the same time, developing a generic unsupervised segmentation algorithm that can be accurately applied to all, or even many, types of […]