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Online news reading has become very popular as the web provides access to news articles from millions of sources around the world. A key challenge of news websites is to help users find the articles that are interesting to read. In this paper, we present our research on developing personalized news recommendation system in Google News. For users who are(More)
The web has become an important medium for news delivery and consumption. Fresh content about a variety of topics and events is constantly being created and published on the web by many sources. As intuitively understood by readers, and studied in journalism, news articles produced by different social groups present different attitudes towards and(More)
Using content-specific models to guide information retrieval and extraction can provide richer interfaces to end-users for both understanding the context of news events and navigating related news articles. In this paper we discuss a system, Brussell, that uses semantic models to organize retrieval and extraction results, generating both storylines(More)
Comparing and contrasting is an important strategy people employ to understand new situations and create solutions for new problems. Similar events can provide hints for problem solving, as well as larger contexts for understanding the specific circumstances of an event. Lessons can be learned from past experience, insights can be gained about the new(More)
We present CRAFT (Collaborative Reasoning and Analysis Framework and Toolkit), a tool for collaborative investigation, reasoning, and analysis. Analysts use CRAFT to represent their collective knowledge and reasoning via interconnected graphical models built upon a shared evolving ontology. These semantic models help connect analysts to digital information(More)
Online news is a rich information resource for learning about new, ongoing, and past events. Intelligence analysts, news junkies, and ordinary people all track developments in ongoing situations as they unfold over time and initiate queries to learn more about the past context of the events of interest to them. Brussell/STT (Situation Tracking Testbed) is(More)
We propose a machine learning system that learns to choose human gestures to accompany novel text. The system is trained on scripts comprised of speech and animations that were hand-coded by professional animators and shipped in video games. We treat this as a text-classification problem, classifying speech as corresponding with specific classes of(More)
Blogs have become an important medium for people to express opinions and share information on the web. Predicting the interests of bloggers can be beneficial for information retrieval and knowledge discovery in the blogosphere. In this paper, we propose a two-layer classification model to categorize the interests of bloggers based on a set of short snippets(More)
Blogs have become an important medium for people to publish opinions and ideas on the web. Bloggers with interest and expertise in specific domains (e.g., politics, or technology) often create and maintain blogs to publish news, opinions and ideas about those domains. In this paper, we present Spectrum, a novel blog search system that enables users to(More)