Connectionists: [Corpora-List] EACL 2014 Tutorial on Computational modelling of metaphor

[peter ljunglöf]

CALL FOR PARTICIPATION

EACL 2014 Tutorial on Computational modelling of metaphor  

Gothenburg, Sweden, 26 April
http://eacl2014.org/tutorial-metaphor

Instructors: Ekaterina Shutova and Tony Veale

 TUTORIAL DESCRIPTION

Metaphor processing is a rapidly growing area in NLP.  Characteristic to all areas of human activity (from the ordinary to the poetic or the scientific) and, thus, to all types of discourse, metaphor poses an important problem for NLP systems. Its ubiquity 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.

Computational work on metaphor in NLP and AI ignited in the 1970s and gained momentum in the 1980s, providing a wealth of ideas on the form, structure and mechanisms of the phenomenon. The last decade has witnessed a technological leap in natural language computation, as manually crafted rules have gradually given 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 resources, these more recent methods boast of a wider coverage, as well as greater efficiency and robustness. However, even the statistical metaphor processing approaches largely focus on a limited domain or a subset of conceptual 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, opens many new avenues for creation of large-scale robust tools for the recognition and interpretation of metaphor.

Despite a growing recognition of the importance of metaphor to the semantic and affective processing of language, and despite the availability of new NLP tools that enable us to take metaphor processing to the next level, educational initiatives for introducing the NLP community to this fascinating area of research have been relatively few in number. Our proposed tutorial thus addresses this gap, by aiming to:

introduce a CL audience to the main linguistic, conceptual and cognitive properties of metaphor;
cover the history of metaphor modelling and the state-of-the-art approaches to metaphor identification and interpretation
analyse the trends in computational metaphor research and compare different types of approaches, aiming to identify the most promising system features and techniques in metaphor modelling
discuss potential applications of metaphor processing in wider NLP
relate the problem of metaphor modelling to that of other types of figurative language

The tutorial is targeted both at participants who are new to the field and need a comprehensive overview of metaphor processing techniques and applications, as well as at experienced scientists who want to stay up to date on the recent advances in metaphor research.


TUTORIAL OUTLINE

Introduction: Linguistic, cognitive and cultural properties of metaphor
Linguistic metaphor
Conceptual metaphor
Metaphorical inference
Extended metaphor / metaphor in discourse
Conventional and novel metaphor
Metaphor in corpora and lexical resources

Computational approaches to metaphor identification
Knowledge-based methods
Lexical resource-based methods
Metaphor and selectional preferences
Metaphor and abstractness
Metaphor and cultural stereotypes
Word similarity and association-based methods
Supervised learning for metaphor identification
Weakly-supervised and unsupervised methods

Computational approaches to metaphor interpretation
Knowledge-based methods
Metaphor interpretation by explanation (SlipNet)
Metaphor interpretation as paraphrasing (supervised and unsupervised)
Challenges in metaphor generation

Applications of metaphor processing systems
Metaphor in machine translation 
Metaphor in opinion mining
Metaphor in information retrieval
Metaphor in educational applications
Metaphor in social science
Metaphor in psychology

Metaphor and other types of figurative language
Metaphor and blending
Metaphor and simile
Metaphor and analogy
Metaphor and irony



We look forward to seeing you at the tutorial!

Katia and Tony

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