Matches in ScholarlyData for { ?s ?p ?o. }
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- talk label "Paper presentation: Seeing the Best and Worst of Everything on the Web with a Two-level, Feature-rich Affect Lexicon".
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- talk label "Paper presentation: The Impact of Visual Appearance on User Response in Online Display Advertising".
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- talk label "Paper presentation: PAC'nPost: A Framework for a Micro-Blogging Social Network in an Unstructured P2P Network".
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- talk label "Paper presentation: Fast and Cost-efficient Bid Estimation for Contextual Ads".
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- talk label "Paper presentation: Textual and Contextual Patterns for Sentiment Analysis over Microblogs".
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- talk label "Paper presentation: Learning from Positive and Unlabeled Amazon Reviews: Towards Identifying Trustworthy Reviewers".
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- talk label "Paper presentation: Lexical Quality as a Proxy for Web Text Understandability".
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- talk label "Paper presentation: News Comments Generation via Mining MicroBlogs".
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- talk label "Paper presentation: Potential Good Abandonment Prediction".
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- talk label "Paper presentation: All Our Messages Are Belong to Us: Usable Confidentiality in Social Networks".
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- talk label "Paper presentation: Extracting Advertising Keywords from URL Strings".
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- talk label "Paper presentation: Entity based Translation Language Model".
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- talk label "Paper presentation: Comparative Evaluation of JavaScript Frameworks".
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- talk label "Paper presentation: TEM: A Novel Perspective to Modeling Content onMicroblogs".
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- talk label "Paper presentation: GPU-Based Minwise Hashing".
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- talk label "Paper presentation: A Data-Driven Sketch of Wikipedia Editors".
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- talk label "Paper presentation: GoThere: Travel Suggestions using Geotagged Photos".
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- talk label "Paper presentation: Using Toolbar Data to Understand Yahoo! Answers Usage".
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- talk label "Paper presentation: The Effect of Links on Networked User Engagement".
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- talk label "Paper presentation: Exploiting Shopping and Reviewing Behavior to Re-score Online Evaluations".
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- talk label "Paper presentation: Treehugger or Petrolhead?".
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- talk label "Paper presentation: Using Proximity to Predict Activity in Social Networks".
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