Title:
Storylines: Computational Models for Big Data
Date:
30/10/2015
Town:
Pisa
Venue:
ILC-CNR – Aula Seminari IBF SG 5
Description:
This talk will present the principles and the pending issues related to the creation of storylines from huge amounts of textual data following the Big Data paradigm. A storyline is best described as a structured index of event descriptions, associated participants, and opinions chronologically ordered and with respect to a certain topic. The talk will be divided in two parts: in the first one, the notion of storyline will be described together with a first version of the computational model which informs its representation and implementation. In the second part, some of the issues related to the actual realisation of the model will be presented through experimental results.
Speaker(s):
Tommaso Caselli
Postdoctoral Fellow (Senior Researcher) at the Computational Lexicology & Terminology Lab at the VU University Amsterdam.
He received his PhD in Computational Linguistics on temporal processing of texts from the University of Pisa in 2009. He has been involved in research in NLP since 2006. His main research areas are in discourse processing, temporal relations and (event) sentiment analysis. He is currently working on the SPINOZA-NWO Project “Understanding Language by Machines – Stories and world views as a key to understanding language”, which aims at developing computational models and NLP tools for storyline extraction from news. He took part to the organization of semantic evaluation campaigns in NLP for English and Italian (SemEval 2010 TempEval-2; EVALITA 2014 EVENTI and SemEval 2015 CLIPEval). His work has been presented at EMNLP, COLING, LREC and elsewhere.
Presentations: