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Prior work on criminal incident prediction has relied primarily on the historical crime record and various geospatial and demographic information sources. Although promising, these models do not take into account the rich and rapidly expanding social media context that surrounds incidents of interest. This paper presents a preliminary investigation of(More)
Law enforcement agencies need crime forecasts to support their tactical operations; namely, predicted crime locations for next week based on data from the previous week. Current practice simply assumes that spatial clusters of crimes or ''hot spots'' observed in the previous week will persist to the next week. This paper introduces a multivariate prediction(More)
The paper studies a large class of bounded-rationality, probabilistic learning models on strategic-form games. The main assumption is that players ''recognize'' cyclic patterns in the observed history of play. The main result is convergence with probability one to a fixed pattern of pure strategy Nash equilibria, in a large class of ''simple games'' in(More)
In this paper, we present a rule-based approach to the inference of elders' activity in two primary application areas: detecting Independent Activities of Daily Living (IADLs) for the detection of anomalies in activity data patterns consistent with arising health issues over a period of time, and the detection of possible emergency conditions passively and(More)