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While a variety of search and retrieval paradigms exist, semantic search has become a popular topic of interest for addressing the shortcomings of current technology. Ontology-driven semantic search, in particular, shows promise in increasing speed and accuracy of document indexing and retrieval. The majority of ontological search systems, however, focus(More)
This paper describes the Spyglass tool, which is designed to help analysts explore very large collections of unstructured text documents. Spyglass uses a domain ontology to index documents, and provides retrieval and visualization services based on the ontology and the resulting index. The ontol-ogy based approach allows analysts to share information and(More)
This paper explores whether the addition of costly, imperfect , and exploitable advisors to Berg's investment game enhances or detracts from investor performance in both one-shot and multi-round interactions. We then leverage our findings to develop an automated investor agent that performs as well as or better than humans in these games. To gather this(More)
Sociological surveys have been a key instrument in understanding social phenomena, but do the introduction and popularity of social media threaten to usurp the survey's place? The significant amount of data one can capture from social media sites like Twitter make such sources appealing. Limited work has tried to triangulate these sources pragmatically for(More)
This work provides a game theoretic framework through which one can study the different trust and mitigation strategies a decision maker can employ when soliciting advice or input from a potentially self-interested third-party. The framework supports a single decision maker's interacting with an arbitrary number of either honest or malicious (and malicious(More)
This paper introduces a general technique, called LABurst, for identifying key moments, or moments of high impact, in social media streams without the need for domain-specific information or seed keywords. We leverage machine learning to model temporal patterns around bursts in Twitter's unfiltered public sample stream and build a classifier to identify(More)
This paper explores whether trust, developed in one context, transfers into another, distinct context and, if so, attempts to quantify the influence this prior trust exerts. Specifically, we investigate the effects of artificially stimulated prior trust as it transfers across disparate contexts and whether this prior trust can compensate for negative(More)