For fans of Computational Linguistics / Natural Language Processing:
---------- Forwarded message ----------
From: Harrington, Jacob Walter
Date: Tue, Oct 11, 2016 at 1:55 PM
Subject: [Cs-ugrads] IVC Seminar, 1pm - 2pm on 10/12, MCS 148
To: "cs-grads@cs.bu.edu" , "cs-ugrads@cs.bu.edu"
Humour, Argument, and Semantics: Learning for Complex Natural Language Tasks
Professor Anna Rumshisky, University of Massachusetts Lowell
Wednesday, October 12 at 1pm in MCS 148
ABSTRACT
In the past few years, deep learning approaches that rely on learned,
rather than engineered feature representations have shown excellent
results in many natural language prediction and classification tasks,
from machine translation to sentiment analysis. Despite the burgeoning
success of models that use attention and memory mechanisms to handle
problems that require deeper reasoning, many complex natural language
tasks still remain out of reach.
In this talk, I will discuss our work on several such tasks, including
computing semantic similarity of text, argumentation mining, and
humour detection. Assessing semantic similarity of text is the holy
grail of language understanding and is at the core of many tough NLP
problems -- such as entailment recognition or paraphrase detection. I
will examine the challenges inherent in this task, present our current
results, and discuss possible solutions. Argumentation mining
involves identifying relations (such as support or attack) between the
claims made in text, and I will discuss our results that apply
attention-based pointer networks to this problem. Finally, humour
detection requires a combination of multiple divergent aspects of
language understanding. I will discuss the effects of integrating
different information and outline future directions.
BIO
Anna Rumshisky is an Assistant Professor of Computer Science at the
University of Massachusetts Lowell, where she heads the Text Machine
Lab for NLP. Her primary research area is natural language
processing, with applications in computational lexical semantics,
temporal reasoning, and clinical informatics, as well as digital
humanities and social science. She received her PhD from Brandeis
University and completed postdoctoral training at MIT CSAIL. Her work
has been funded by National Institutes of Health, Army Research
Office, and other government and industry grants.
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