25.4684, Calls: Text/Corpus Ling, Computational Ling, Semantics, Applied Ling/USA

Thu Nov 20 22:30:43 UTC 2014

LINGUIST List: Vol-25-4684. Thu Nov 20 2014. ISSN: 1069 - 4875.

Subject: 25.4684, Calls: Text/Corpus Ling, Computational Ling, Semantics, Applied Ling/USA

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Date: Thu, 20 Nov 2014 17:30:25
From: Ekaterina Shutova [katia at icsi.berkeley.edu]
Subject: 3rd Workshop on Metaphor in NLP

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Full Title: 3rd Workshop on Metaphor in NLP 

Date: 05-Jun-2015 - 05-Jun-2015
Location: Denver, Colorado, USA 
Contact Person: Ekaterina Shutova
Meeting Email: katia at icsi.berkeley.edu
Web Site: https://sites.google.com/site/metaphorinnlp2015/home 

Linguistic Field(s): Applied Linguistics; Computational Linguistics; Semantics; Text/Corpus Linguistics 

Call Deadline: 04-Mar-2015 

Meeting Description:

The Third Workshop on Metaphor in NLP (co-located with NAACL 2015)
Denver, Colorado, USA – June 5, 2015
https://sites.google.com/site/metaphorinnlp2015/home

Workshop Description:

Metaphor processing is a rapidly growing area in natural language processing (NLP). The ubiquity of metaphor in language has been established in a number of corpus studies and the role it plays in human reasoning has been confirmed in psychological experiments. This makes metaphor an important research area for computational and cognitive linguistics, and its automatic identification and interpretation indispensable for any semantics-oriented NLP application.

The work on metaphor in NLP and AI started in the 1980s, providing us with a wealth of ideas on its structure and mechanisms. The last decade witnessed a technological leap in natural language computation, whereby manually crafted rules gradually give way to more robust corpus-based statistical methods. This is also the case for metaphor research. In the recent years, the problem of metaphor modeling has been steadily gaining interest within the NLP community, with a growing number of approaches exploiting statistical techniques. Compared to more traditional approaches based on hand-coded knowledge, these more recent methods tend to have a wider coverage, as well as be more efficient, accurate and robust. However, even the statistical metaphor processing approaches so far often focused on a limited domain or a subset of phenomena. At the same time, recent work on computational lexical semantics and lexical acquisition techniques, as well as a wide range of NLP methods applying machine learning to open-domain semantic tasks, open many new avenues for creation of large-scale robust tools for recognition and interpretation of metaphor.

The main focus of the workshop will be on computational modeling of metaphor using state-of-the-art NLP techniques. However, papers on cognitive, linguistic, and applied aspects of metaphor are also of interest, provided that they are presented within a computational, a formal or a quantitative framework. We also encourage descriptions of proposals and data sets for shared tasks on metaphor processing.

Call for Papers:

Submission deadline: March 4, 2015

The workshop will solicit both full papers and short papers for either oral or poster presentation.

Topics will include, but will not be limited to, the following:

Identification and interpretation of different levels and types of metaphor:
Conceptual and linguistic metaphor
Lexical metaphor
Multiword metaphorical expressions
Extended metaphor / metaphor in discourse
Conventional / novel / deliberate metaphor

Metaphor processing systems that incorporate state-of-the-art NLP methods:

Statistical metaphor processing
The use of lexical resources for metaphor processing
The use of corpora for metaphor processing
Distributional methods for metaphor processing
Supervised and unsupervised learning for metaphor processing
Identification of conceptual and linguistic metaphor
Identification and interpretation of lexical metaphor / multiword metaphor / extended metaphor
Lexical metaphor interpretation vs. word sense disambiguation
Metaphor paraphrasing
Generation of metaphorical expressions
Metaphor translation and multilingual metaphor processing

Metaphor resources and evaluation:

Metaphor annotation in corpora
Metaphor in lexical resources
Reliability of metaphor annotation
Datasets for evaluation of metaphor processing tools
Metaphor evaluation methodologies and frameworks
Descriptions of proposals for shared tasks on metaphor processing

Metaphor processing for external NLP applications:

Metaphor in machine translation
Metaphor in opinion mining
Metaphor in information retrieval
Metaphor in educational applications
Metaphor in dialog systems
Metaphor in open-domain and domain-specific applications

Metaphor and cognition:

Computational approaches to metaphor inspired by cognitive evidence
Cognitive models of metaphor processing by the human brain
Models of metaphor across languages and cultures

Metaphor interaction with other phenomena (within a computational, formal or quantitative framework):

Metaphor and compositionality
Metaphor and abstractness / concreteness
Metaphor and sentiment
Metaphor and persuasion
Metaphor and argumentation
Metaphor and metonymy
Metaphor and grammar

Metaphor and sentiment:

The use of metaphorical language to express stronger sentiment / evaluation
Sentiment processing systems that make use of metaphor as a feature
Sentiment processing systems that detect affect associated with metaphorical expressions

Metaphor in social media:

Processing of metaphorical language in blogging, twitter and other social media
How metaphorical language helps shape communication in social media
The influence of metaphor on social dynamics

Important Dates:

March 4, 2015: Paper submissions due (23:59 East Coast USA time)
March 23, 2015: Notification of acceptance
March 30, 2015: Camera-ready papers due
June 5, 2015: Workshop in Denver, Colorado, USA

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