Cody Buntain

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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 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)
Twitter can be a rich source of information when one wants to monitor trends related to a given topic. In this paper, we look at how tweets can augment a public health program that studies emerging patterns of illicit drug use. We describe the architecture necessary to collect vast numbers of tweets over time based on a large number of search terms and the(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)
Social media sites like Twitter provide readily accessible sources of large-volume, high-velocity data streams, now referred to as “Big Data.” While private companies have already made great strides in leveraging these social media sources, many public organizations and government agencies could reap significant benefits from these resources. Care must be(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 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)
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 ontology based approach allows analysts to share information and(More)