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Social Sensing by Lance Kaplan, Tarek Abdelzaher, Dong Wang

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Chapter 10

Recursive fact-finding

Abstract

As we discussed earlier in Chapter 5, expectation maximization (EM) is an iterative algorithm that provides the maximum likelihood estimation when the iteration converges. However, running the iterative algorithm is not necessarily efficient for the streaming data, especially when the estimation parameter θ remains stable over time. This observation motivates the development of a real-time version of the EM algorithm for streaming data to achieve a better tradeoff between the estimation accuracy and running time. In this chapter, we present a recursive fact-finding model developed based on EM approach that allows the applications to update their estimation on the fly as data stream in.

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