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Computational Linguistics and Information Processing
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== 10/10/2012: Beyond MaltParser - Advances in Transition-Based Dependency Parsing == | |||
'''Speaker:''' Joakim Nivre , Uppsala University / Google<br/> | |||
'''Time:''' Wednesday, October 10, 2012, 11:00 AM<br/> | |||
'''Venue:''' AVW 3258<br/> | |||
'''Abstract:''' The transition-based approach to dependency parsing has become | |||
popular thanks to its simplicity and efficiency. Systems like MaltParser | |||
achieve linear-time parsing with projective dependency trees using locally | |||
trained classifiers to predict the next parsing action and greedy best-first | |||
search to retrieve the optimal parse tree, assuming that the input sentence has | |||
been morphologically disambiguated using a part-of-speech tagger. In this talk, | |||
I survey recent developments in transition-based dependency parsing that address | |||
some of the limitations of the basic transition-based approach. First, I show | |||
how globally trained classifiers and beam search can be used to mitigate error | |||
propagation and enable richer feature representations. Secondly, I discuss | |||
different methods for extending the coverage to non-projective trees, which are | |||
required for linguistic adequacy in many languages.Finally, I present a | |||
model for joint tagging and parsing that leads to improvements in both tagging | |||
and parsing accuracy as compared to the standard pipeline approach. | |||
'''About the Speaker:''' Joakim Nivre is Professor of Computational Linguistics at Uppsala | |||
University and currently visiting scientist at Google, New York. He holds a | |||
Ph.D. in General Linguistics from the University of Gothenburg and a Ph.D. in | |||
Computer Science from Växjö University. Joakim's research focuses on data-driven | |||
methods for natural language processing, in particular for syntactic and semantic analysis. He is one of the main developers of the transition-based | |||
approach to syntactic dependency parsing, described in his 2006 book Inductive | |||
Dependency Parsing and implemented in the MaltParser system. Joakim?s current | |||
research interests include the analysis of mildly non-projective dependency | |||
structures, the integration of morphological and syntactic processing for richly | |||
inflected languages, and methods for cross-framework parser evaluation. He has | |||
produced over 150 scientific publications, including 3 books, and has given | |||
nearly 70 invited talks at conferences and institutions around the world. He is | |||
the current secretary of the European Chapter of the Association for | |||
Computational Linguistics. | |||
'''Host:''' Doug Oard, oard@umd.edu | |||
== 10/03/2012: Shay Cohen == | == 10/03/2012: Shay Cohen == | ||
Line 21: | Line 58: | ||
== 09/05/2012: 5 Minute Madness (Part I) == | == 09/05/2012: 5 Minute Madness (Part I) == | ||
== 08/20/2012: TopSig – Signature Files Revisited | == 08/20/2012: TopSig – Signature Files Revisited == | ||
'''Speaker:''' Shlomo Geva, Queensland University of Technology, Australia<br/> | '''Speaker:''' Shlomo Geva, Queensland University of Technology, Australia<br/> | ||
'''Time:''' Monday August 20, 11:00 AM<br/> | '''Time:''' Monday, August 20, 2012, 11:00 AM<br/> | ||
'''Venue:''' AVW | '''Venue:''' AVW 2120<br/> | ||
'''Abstract:''' Performance comparisons between File Signatures and Inverted | '''Abstract:''' Performance comparisons between File Signatures and Inverted | ||
Files for text retrieval have previously shown several | Files for text retrieval have previously shown several | ||
significant shortcomings of file signatures relative to inverted | significant shortcomings of file signatures relative to inverted | ||
files. The inverted file approach underpins most state-of- | files. The inverted file approach underpins most state-of-the-art | ||
search engine algorithms, such as Language and Probabilistic | search engine algorithms, such as Language and Probabilistic | ||
models. It has been widely accepted that traditional | models. It has been widely accepted that traditional | ||
Line 58: | Line 95: | ||
'''Host:''' Doug Oard, oard@umd.edu | '''Host:''' Doug Oard, oard@umd.edu | ||
== Talks | == Previous Talks == | ||
* [[CLIP Colloquium (Spring 2012)|Spring 2012]] | * [[CLIP Colloquium (Spring 2012)|Spring 2012]] | ||
* [[CLIP Colloquium (Fall 2011)|Fall 2011]] | * [[CLIP Colloquium (Fall 2011)|Fall 2011]] | ||
* [[CLIP Colloquium (Spring 2011)|Spring 2011]] | * [[CLIP Colloquium (Spring 2011)|Spring 2011]] | ||
* [[CLIP Colloquium (Fall 2010)|Fall 2010]] | * [[CLIP Colloquium (Fall 2010)|Fall 2010]] |
Revision as of 22:11, 23 August 2012
The CLIP Colloquium is a weekly speaker series organized and hosted by CLIP Lab. The talks are open to everyone. Most talks are held at 11AM in AV Williams 3258 unless otherwise noted. Typically, external speakers have slots for one-on-one meetings with Maryland researchers before and after the talks; contact the host if you'd like to have a meeting.
If you would like to get on the cl-colloquium@umiacs.umd.edu list or for other questions about the colloquium series, e-mail Jimmy Lin, the current organizer.
{{#widget:Google Calendar
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|color=B1440E
|title=Upcoming Talks
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10/10/2012: Beyond MaltParser - Advances in Transition-Based Dependency Parsing
Speaker: Joakim Nivre , Uppsala University / Google
Time: Wednesday, October 10, 2012, 11:00 AM
Venue: AVW 3258
Abstract: The transition-based approach to dependency parsing has become popular thanks to its simplicity and efficiency. Systems like MaltParser achieve linear-time parsing with projective dependency trees using locally trained classifiers to predict the next parsing action and greedy best-first search to retrieve the optimal parse tree, assuming that the input sentence has been morphologically disambiguated using a part-of-speech tagger. In this talk, I survey recent developments in transition-based dependency parsing that address some of the limitations of the basic transition-based approach. First, I show how globally trained classifiers and beam search can be used to mitigate error propagation and enable richer feature representations. Secondly, I discuss different methods for extending the coverage to non-projective trees, which are required for linguistic adequacy in many languages.Finally, I present a model for joint tagging and parsing that leads to improvements in both tagging and parsing accuracy as compared to the standard pipeline approach.
About the Speaker: Joakim Nivre is Professor of Computational Linguistics at Uppsala University and currently visiting scientist at Google, New York. He holds a Ph.D. in General Linguistics from the University of Gothenburg and a Ph.D. in Computer Science from Växjö University. Joakim's research focuses on data-driven methods for natural language processing, in particular for syntactic and semantic analysis. He is one of the main developers of the transition-based approach to syntactic dependency parsing, described in his 2006 book Inductive Dependency Parsing and implemented in the MaltParser system. Joakim?s current research interests include the analysis of mildly non-projective dependency structures, the integration of morphological and syntactic processing for richly inflected languages, and methods for cross-framework parser evaluation. He has produced over 150 scientific publications, including 3 books, and has given nearly 70 invited talks at conferences and institutions around the world. He is the current secretary of the European Chapter of the Association for Computational Linguistics.
Host: Doug Oard, oard@umd.edu
10/03/2012: Shay Cohen
09/19/2012: Earl Wagner
09/12/2012: 5 Minute Madness (Part II)
09/05/2012: 5 Minute Madness (Part I)
08/20/2012: TopSig – Signature Files Revisited
Speaker: Shlomo Geva, Queensland University of Technology, Australia
Time: Monday, August 20, 2012, 11:00 AM
Venue: AVW 2120
Abstract: Performance comparisons between File Signatures and Inverted Files for text retrieval have previously shown several significant shortcomings of file signatures relative to inverted files. The inverted file approach underpins most state-of-the-art search engine algorithms, such as Language and Probabilistic models. It has been widely accepted that traditional file signatures are inferior alternatives to inverted files. This paper describes TopSig, a modern approach to the construction of file signatures - many advances in semantic hashing and dimensionality reduction have been made in recent times, but these were not so far linked to general purpose, signature file based, search engines. This paper introduces a different signature file approach that builds upon and extends these recent advances. We are able to demonstrate significant improvements in the performance of signature file based indexing and retrieval, performance that is comparable to that of state of the art inverted file based systems, including Language models and BM25. These findings suggest that file signatures offer a viable alternative to inverted files in suitable settings and position the file signature model in the class of Vector Space retrieval models. TopSig is an open-source search engine from QUT and it can be discussed too if there is an interest.
About the Speaker: Associate Professor Shlomo Geva is the discipline leader for Computational Intelligence and Signal Processing in the Computer Science Department at the Queensland University of Technology in Brisbane, Australia. His research interests include clustering, cross-language information retrieval, focused information retrieval, link discovery, and xml indexing.
Host: Doug Oard, oard@umd.edu