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This paper describes the participation of FEUP, from the University of Porto, in the TREC 2009 Blog Track. FEUP participated in the faceted blog distillation task with work focused on the use of temporal features available in the new TREC Blogs08 collection. The approach presented in this paper uses the temporal information available in most individual posts to amplify (or reduce) each post's score. Blog scores, and subsequent ranks, are obtained by combining individual posts' scores. While preparing the runs, no endeavors were made to identify a priori any temporal differences between the three distinct facets.

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Narratives are present in many forms of human expression and can be understood as a fundamental way of communication between people. Computational understanding of the underlying story of a narrative, however, may be a rather complex task for both linguists and computational linguistics. Such task can be approached using natural language processing techniques to automatically extract narratives from texts. In this paper, we present an in depth survey of narrative extraction from text, providing a establishing a basis/framework for the study roadmap to the study of this area as a whole as a means to consolidate a view on this line of research. We aim to fulfill the current gap by identifying important research efforts at the crossroad between linguists and computer scientists. In particular, we highlight the importance and complexity of the annotation process, as a crucial step for the training stage. Next, we detail methods and approaches regarding the identification and extraction of narrative components, their linkage and understanding of likely inherent relationships, before detailing formal narrative representation structures as an intermediate step for visualization and data exploration purposes. We then move into the narrative evaluation task aspects, and conclude this survey by highlighting important open issues under the domain of narratives extraction from texts that are yet to be explored.