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BEGIN:VEVENT
DTSTAMP:20260513T233649Z
DTSTART;VALUE=DATE-TIME:20180518T110000
DTEND;VALUE=DATE-TIME:20180518T120000
SUMMARY:Yulan He: Unsupervised Event Extraction and Storyline Generation 
 from Text
TZID:Europe/London
UID:20180518-8a17841a62f756b10162fbf501e34706@warwick.ac.uk
CREATED:20180425T083920Z
DESCRIPTION:Abstract: Newsworthy events are widely scattered not only on 
 traditional news media but also on social media. In this talk\, I will p
 resent a series of unsupervised Bayesian model for the extraction of str
 uctured representations of events from Twitter without the use of any la
 belled data. The extracted events are automatically clustered into coher
 ence event type groups. In addition\, event extraction and visualisation
  are jointly modelled to allow simultaneous extraction of events and vis
 ualisation of both events and tweets. To deal with lexical variations of
  certain named entities\, word embeddings are incorporated into model le
 arning. Moreover\, to automatically infer the number of events from the 
 data\, the Dirichlet process mixture model is used for event generation.
  Related events published in temporal proximity could be linked to form 
 a storyline which allows a quick glimpse of event evolution over time. I
  will also present two models for storyline generation from news article
 s. The first one is a non-parametric generative model which extracts str
 uctured representations and evolution patterns of storylines simultaneou
 sly. The second one is the neural storyline generation model which appro
 ximates storyline distributions using neural networks and explores the s
 imilarity revealed by the title and the main body of a news article and 
 also temporally-related news articles. Short bio: Yulan He is a Reader i
 n Computer Science and the Director of the Systems Analytics Research In
 stitute at Aston University\, UK. She is experienced in statistical mode
 lling and text mining\, particularly the integration of machine learning
  and natural language processing for social media analysis. She has publ
 ished over 150 papers on topics including sentiment analysis\, informati
 on extraction\, clinical text mining\, recommender systems\, learning an
 alytics and spoken dialogue systems. She served as an Area Chair in ACL 
 2018\, EMNLP 2018\, NAACL 2016\, EMNLP 2015\, CCL 2015 and NLPCC 2015 an
 d co-organised ECIR 2010 and PRIB 2007. She obtained her PhD degree in s
 poken language understanding from the University of Cambridge.
LOCATION:CS104
CATEGORIES:
LAST-MODIFIED:20180516T144040Z
ORGANIZER;CN=Sara Kalvala:
END:VEVENT
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