10 research outputs found
What is behind a summary-evaluation decision?
Research in psychology has reported that, among the variety of possibilities for assessment methodologies, summary evaluation offers a particularly adequate context for inferring text comprehension and topic understanding. However, grades obtained in this methodology are hard to quantify objectively. Therefore, we carried out an empirical study to analyze the decisions underlying human summary-grading behavior. The task consisted of expert evaluation of summaries produced in critically relevant contexts of summarization development, and the resulting data were modeled by means of Bayesian networks using an application called Elvira, which allows for graphically observing the predictive power (if any) of the resultant variables. Thus, in this article, we analyzed summary-evaluation decision making in a computational framewor
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Heuristic search in symbolic probability inference
I present a new heuristic search approach to compute approximate answers for the probability query in belief nets. This approach can compute the 'best' bounds for a query in a period of any given time (if time permitted, it will get an exact value). It inherits the essence of Symbolic Probabilistic Inference (SPI), which is the factoring part of SPI, and searches the structure passed by SPI to find a approximate value. This paper also presents the theoretical background for this approach. Empirical results are presented for three heuristics of this approach and a best first search approach tested in a set of randomly generated belief nets and a net from the real world