|e-mail for homeworks etc:||Jirka.LastName@gmail.com (start the email's subject with NPFL128)|
|Time & Place:||Wed 15:40-17:10 S8|
The course surveys solutions to common NLP tasks ranging from entity recognition to text generation. It evaluates various approaches (machine learning, rules, larger resources, ...) and their combinations.
Most of the course consists of students presenting and discussing papers relevant to a given topic. Part of the course is also implementation of a prototype system, typically replicating one described in one of the papers.
This course is organized as a discussion of important papers. Everybody reads all the papers to be able to participate in the discussion. For each paper, one student will be responsible for leading the discussion.
There is one programming [Project] due on July 31 (talk to me if you cannot meet the deadline). Note that using git and Pull requests is required.
|Active class participation||0-50|
|Discussion on||Summary by||Topic||Related/Other papers|
Intro to Computational Morphology: [slides]
A. Feldman & J. Hana (2010). A resource-light approach to morpho-syntactic tagging (Chapter 6, 7) [slides]
|2 Mar||Jacob||D. Yarowsky & R. Wicentowski (2000): Minimally Supervised Morphological Analysis by Multimodal Alignment||R. Wicentowski (2004): Multilingual noise-robust supervised morphological analysis using the WordFrame model|
|9 Mar||Dominika||J. Goldsmith (2001). Unsupervised Learning of the Morphology of a Natural Language.||Linguistica website|
|16 Mar||Kristýna||P. Schone & D. Jurafsky (2001): Knowledge-free induction of inflectional morphologies||P. J. Schone (2001): Toward knowledge-free induction of machine-readable dictionaries.|
|Andrew||J. Shlens: A Tutorial on Principal Component Analysis|
|23 Mar||Rishu||J. Pennington, R. Socher, C. Manning: GloVe: Global Vectors for Word Representation|
|Jan||Kohonen, Virpioja and Lagus (2010): Semi-supervised learning of concatenative morphology.|
S. Cucerzan & D. Yarowsky (2002): Bootstrapping a Multilingual Part-of-speech Tagger in One Person-day
_ (2003): Minimally Supervised Induction of Grammatical Gender
|6 Apr||Nalin + Goutham||Albert Gatt, Emiel Krahmer (2018): Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation|
|13 Apr||Antonije||Marco Tulio Ribeiro, Tongshuang Wu, Carlos Guestrin, and Sameer Singh (2020): Beyond Accuracy: Behavioral Testing of NLP Models with CheckList.|
|20 Apr||Igbal||Bing Liu (2017): Many Facets of Sentiment Analysis|
|Anna||Saif M. Mohammad (2017): Challenges in Sentiment Analysis|
|27 Apr||Daniela||D. Nadeau & S. Sekine (2007): A survey of named entity recognition and classification|
|Daragh||Named Entity Recognition - Cucerzan (2007). Large-Scale Named Entity Disambiguation Based on Wikipedia Data|
|4 May||Amrita||Mihai Surdeanu, David McClosky, Mason R. Smith, Andrey Gusev, and Christopher D. Manning. 2011. Customizing an Information Extraction System to a New Domain|
|Borek||Steven Feng et al (2021): A Survey on Data Augmentation Approaches for NLP|
|11 May||NO CLASS|
|18 May||NO CLASS|
E2E NLG Challenge:
Juraska et al (2018): Slug2Slug: A Deep Ensemble Model with Slot Alignment for Sequence-to-Sequence Natural Language Generation;
Nguyen & Tran (2018): Structure-based Generation System for E2E NLG Challenge
|Alexander||Named Entity Recognition - Gao & Cucerzan (2017). Entity Linking to One Thousand Knowledge Bases. ECIR.|