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Institute of Applied Data Science

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Professor Massimo Poesio

Massimo Poesio

Professor of Computational Linguistics & Turing Fellow

Department School of Electronic Engineering and Computer Science
 Peter Landin, CS 404
+44 20 7882 5773

www.eecs.qmul.ac.uk/profiles/poesiomassimo.html

Research

Natural Language Processing, machine translation, visually grounded and textual semantic models

Interests

His research interests are in the semantics of natural language and in computational methods for semantic analysis, particularly in the areas of anaphora resolution and in dialogue. One of the main areas of research at the moment is the use of games to collect data to support computational linguistics (‘Games with a purpose’). His work on the organisation and acquisition of conceptual knowledge has involved using machine learning techniques to acquire evidence about common sense from corpora and brain data. 

Publications

Publications of specific relevance to Applied Data Science

2020

Alhelbawy A, Lattimer M, Kruschwitz U, Fox C and Poesio M (2020). An NLP-Powered Human Rights Monitoring Platform. Expert Systems With Applications  vol. 153, 10.1016/j.eswa.2020.113365
Fornaciari T, Cagnina L, Rosso P and Poesio M (2020). Fake opinion detection: how similar are crowdsourced datasets to real data? Language Resources and Evaluation  10.1007/s10579-020-09486-5

2019

Uryupina O, Artstein R, Bristot A, Cavicchio F, Delogu F, Rodriguez KJ and Poesio M (2019). Annotating a broad range of anaphoric phenomena, in a variety of genres: The ARRAU Corpus. Natural Language Engineering  10.1017/S1351324919000056

2018

Chamberlain J, Kruschwitz U and Poesio M (2018). Optimising crowdsourcing efficiency: Amplifying human computation with validation. Walter De Gruyter Gmbh  It - Information Technology  vol. 60, (1) 41-49. 10.1515/itit-2017-0020

2017

POESIO M, ANDERSON A, Clark S and Kiela D (2017). Visually grounded and textual semantic models differentially decode brain activity associated with concrete and abstract nouns. Association For Computational Linguistics  Transactions of The Association For Computational Linguistics  vol. 5, 17-30.

2016

Ginzburg J and Poesio M (2016). Grammar Is a System That Characterizes Talk in Interaction. Frontiers Media  Front Psychol  vol. 7, 1938-1938. 10.3389/fpsyg.2016.01938
Rieser H and Poesio M (2016). Pandora's Box Opened. Theoretical Linguistics  vol. 42, (3-4) 305-318. 10.1515/tl-2016-0015

2015

Anderson AJ, Bruni E, Lopopolo A, Poesio M and Baroni M (2015). Reading visually embodied meaning from the brain: Visually grounded computational models decode visual-object mental imagery induced by written text. Neuroimage  vol. 120, 309-322. 10.1016/j.neuroimage.2015.06.093
Sikdar UK, Ekbal A, Saha S, Uryupina O and Poesio M (2015). Differential evolution-based feature selection technique for anaphora resolution. Soft Computing  vol. 19, (8) 2149-2161. 10.1007/s00500-014-1397-3

2014

Anderson AJ, Murphy B and Poesio M (2014). Discriminating taxonomic categories and domains in mental simulations of concepts of varying concreteness. Journal of Cognitive Neuroscience  vol. 26, (3) 658-681. 10.1162/jocn_a_00508
Cavicchio F, Melcher D and Poesio M (2014). The effect of linguistic and visual salience in visual world studies. Frontiers in Psychology  vol. 5, (MAR) 10.3389/fpsyg.2014.00176

2013

Fornaciari T and Poesio M (2013). Automatic deception detection in Italian court cases. Artificial Intelligence and Law  vol. 21, (3) 303-340. 10.1007/s10506-013-9140-4
Sikdar UK, Ekbal A, Saha S, Uryupina O and Poesio M (2013). Anaphora resolution for bengali: An experiment with domain adaptation. Computacion Y Sistemas  vol. 17, (2) 137-146.
Poesio M, Chamberlain J, Kruschwitz U, Robaldo L and Ducceschi L (2013). Phrase detectives: Utilizing collective intelligence for internet-scale language resource creation. Acm Transactions On Interactive Intelligent Systems  vol. 3, (1) 10.1145/2448116.2448119
Chamberlain J, Kruschwitz U and Poesio M (2013). Methods for engaging and evaluating users of human computation systems. Handbook of Human Computation  10.1007/978-1-4614-8806-4_54

2012

Akama H, Murphy B, Na L, Shimizu Y and Poesio M (2012). Decoding semantics across fMRI sessions with different stimulus modalities: A practical MVPA study. Frontiers in Neuroinformatics  vol. 6, (JULY 2012) 10.3389/fninf.2012.00024
Cavicchio F and Poesio M (2012). (Non)cooperative dialogues: The role of emotions. Human Factors  vol. 54, (4) 546-559. 10.1177/0018720812440279
Cavicchio F and Poesio M (2012). The Rovereto Emotion and Cooperation Corpus: A new resource to investigate cooperation and emotions. Language Resources and Evaluation  vol. 46, (1) 117-130. 10.1007/s10579-011-9163-y

2011

Poesio M, Diewald N, Stührenberg M, Chamberlain J, Jettka D, Goecke D and Kruschwitz U (2011). Markup infrastructure for the anaphoric bank: Supporting web collaboration. Studies in Computational Intelligence  vol. 370, 175-195. 10.1007/978-3-642-22613-7_10
Murphy B, Poesio M, Bovolo F, Bruzzone L, Dalponte M and Lakany H (2011). EEG decoding of semantic category reveals distributed representations for single concepts. Brain and Language  vol. 117, (1) 12-22. 10.1016/j.bandl.2010.09.013

2010

Baroni M, Murphy B, Barbu E and Poesio M (2010). Strudel: A corpus-based semantic model based on properties and types. Cognitive Science  vol. 34, (2) 222-254. 10.1111/j.1551-6709.2009.01068.x

2009

Poesio M, Day D and Mani I (2009). Janet Hitzeman Obituary. Computational Linguistics  vol. 35, (4) 476-479.
Karamanis N, Poesio M, Mellish C and Oberlander J (2009). Evaluating centering for information ordering using corpora. Computational Linguistics  vol. 35, (1) 29-46. 10.1162/coli.07-036-R2-06-22

2008

Poesio M and Artstein R (2008). Introduction to the special issue on ambiguity and semantic judgments. Research On Language and Computation  vol. 6, (3-4) 241-245. 10.1007/s11168-008-9057-3
Poesio M (2008). Linguistic Claims Formulated in Terms of Centering Linguistic Claims Formulated in Terms of Centering A Re-Examination Using Parametric CB-Tracking Techniques. Reference: Interdisciplinary Perspectives  10.1093/acprof:oso/9780195331639.003.0009
Artstein R and Poesio M (2008). Inter-coder agreement for computational linguistics. Computational Linguistics  vol. 34, (4) 555-596. 10.1162/coli.07-034-R2
Poesio M and Almuhareb A (2008). Extracting concept descriptions from the web: The importance of attributes and values. Frontiers in Artificial Intelligence and Applications  vol. 167, (1) 29-44.

2007

Steinberger J, Poesio M, Kabadjov MA and Ježek K (2007). Two uses of anaphora resolution in summarization. Information Processing and Management  vol. 43, (6) 1663-1680. 10.1016/j.ipm.2007.01.010
Sanchez-Graillet O and Poesio M (2007). Negation of protein-protein interactions: Analysis and extraction. Bioinformatics  vol. 23, (13) 10.1093/bioinformatics/btm184

2006

Poesio M, Sturt P, Artstein R and Filik R (2006). Underspecification and anaphora: Theoretical issues and preliminary evidence. Discourse Processes  vol. 42, (2) 157-175. 10.1207/s15326950dp4202_4

2005

Poesio M (2005). Domain modelling and NLP: Formal ontologies? Lexica? Or a bit of both? Applied Ontology  vol. 1, 27-33.

2004

Poesio M, Di Eugenio B, Stevenson R and Hitzeman J (2004). Centering: A parametric theory and its instantiations. Computational Linguistics  vol. 30, (3) 309-364. 10.1162/0891201041850911

2002

Garrod S and Poesio M (2002). Plumbing semantic depths in Amsterdam. Trends in Cognitive Sciences  vol. 6, (4) 150-151. 10.1016/S1364-6613(02)01878-8

2000

Vieira R and Poesio M (2000). An empirically based system for processing definite descriptions. Computational Linguistics  vol. 26, (4) 539-593. 10.1162/089120100750105948
Vieira R and Poesio M (2000). An empirically based system for processing definite descriptions. Computational Linguistics  vol. 26, (4) 538-593.

1998

Poesio M and Vieira R (1998). A Corpus-based Investigation of Definite Description Use. Computational Linguistics  vol. 24, (2)

1997

Poesio M and Traum DR (1997). Conversational actions and discourse situations. Computational Intelligence  vol. 13, (3) 309-345. 10.1111/0824-7935.00042

1996

Traum DR, Schubert LK, Martin NG, Hwang CH, Heeman P, Ferguson G, Allen JF, Poesio M and Light M (1996). Knowledge representation in the TRAINS-93 conversation system. International Journal of Expert Systems  vol. 9, (1) 173-223.
Poesio M (1996). Logic and lexicon - Pinkal,M. Computational Linguistics  vol. 22, (1) 140-144.

1995

Allen JF, Schubert LK, Ferguson G, Heeman P, Hwang CH, Kato T, Light M, Martin N, Miller B, Poesio M and Traum DR (1995). The TRAINS project: A case study in building a conversational planning agent. Journal of Experimental and Theoretical Artificial Intelligence  vol. 7, (1) 7-48. 10.1080/09528139508953799

1987

Poesio M and Rullent C (1987). MODIFIED CASEFRAME PARSING FOR SPEECH UNDERSTANDING SYSTEMS. Cselt Technical Reports  vol. 15, (6) 441-446.

Grants

Grants of specific relevance to Applied Data Science
Human Rights and Information Technology in the Era of Big Data
Mcgregor L, Bhalotra SR, Woods LM, Poesio M, Landman T, Sunkin M, Mcdonald-Maier KD and Fussey P
£4,743,734 Economic and Social Research Council (30-09-2015 - 29-09-2021)
Summary
Disagreements and Language Interpretation
Poesio M
EUR2,499,471 European Research Council (01-09-2016 - 31-08-2021)
Summary