TextGraphs-5: Graph-based Methods for Natural Language Processing
16th of July 2010, Uppsala, Sweden| 9:00–9:10 | Welcome to TextGraphs 5 |
Session 1: Lexical Clustering and Disambiguation | |
| 09:10–09:30 | Graph-Based Clustering for Computational Linguistics: A Survey Zheng Chen and Heng Ji |
| 09:30–09:50 | Towards the Automatic Creation of a Wordnet from a Term-Based Lexical Network Hugo Gonçalo Oliveira and Paulo Gomes |
| 09:50–10:10 | An Investigation on the Influence of Frequency on the Lexical Organization of Verbs Daniel German, Aline Villavicencio and Maity Siqueira |
| 10:10–10:30 | Robust and Efficient Page Rank for Word Sense Disambiguation Diego De Cao, Roberto Basili, Matteo Luciani, Francesco Mesiano and Riccardo Rossi |
| 10:30–11:00 | Coffee Break |
| 11:00–11:20 | Hierarchical Spectral Partitioning of Bipartite Graphs to Cluster Dialects and Identify Distinguishing Features Martijn Wieling and John Nerbonne |
| 11:20–11:40 | A Character-Based Intersection Graph Approach to Linguistic Phylogeny Jessica Enright |
| 11:40–12:40 | Invited Talk: Spectral Approaches to Learning in the Graph Domain Edwin Hancock |
| 12:40–13:50 | Lunch break |
| 13:50–14:10 | Cross-Lingual Comparison between Distributionally Determined Word Similarity Networks Olof Görnerup and Jussi Karlgren |
| 14:10–14:30 | Co-Occurrence Cluster Features for Lexical Substitutions in Context Chris Biemann |
| 14:30–14:50 | Contextually-Mediated Semantic Similarity Graphs for Topic Segmentation Geetu Ambwani and Anthony Davis |
| 14:50–15:10 | MuLLinG: MultiLevel Linguistic Graphs for Knowledge Extraction Vincent Archer |
| 15:10–15:30 | Experiments with CST-Based Multidocument Summarization Maria Lucia Castro Jorge and Thiago Pardo |
| 15:30–16:00 | Coffee Break |
| 16:00–16:20 | Distinguishing between Positive and Negative Opinions with Complex Network Features Diego Raphael Amancio, Renato Fabbri, Osvaldo Novais Oliveira Jr., Maria das Graças Volpe Nunes and Luciano da Fontoura Costa |
| 16:20–16:40 | Image and Collateral Text in Support of Auto-Annotation and Sentiment Analysis Pamela Zontone, Giulia Boato, Jonathon Hare, Paul Lewis, Stefan Siersdorfer and Enrico Minack |
| 16:40–17:00 | Aggregating Opinions: Explorations into Graphs and Media Content Analysis Gabriele Tatzl and Christoph Waldhauser |
| 17:00–17:20 | Eliminating Redundancy by Spectral Relaxation for Multi-Document Summarization Fumiyo Fukumoto, Akina Sakai and Yoshimi Suzuki |
| 17:20–17:40 | Computing Word Senses by Semantic Mirroring and Spectral Graph Partitioning Martin Fagerlund, Magnus Merkel, Lars Eldén and Lars Ahrenberg |
| 17:40–18:00 | Final Wrap-up |
Invited Talk: Spectral approaches to learning in the graph domain
Prof. Edwin R. HancockThe talk will commence by discussing some of the problems that arise when machine learning is applied to graph structures. A taxonomy of different methods organised around a) clustering b) characterisation and c) constructing generative models in the graph domain will be introduced. With this taxonomy in hand, Dr. Hancock will then describe a number of graph-spectral algorithms that can be applied to solve the many different problems inherent to graphs, drawing examples from computer vision research.
About the speaker
Edwin R. Hancock holds a BS degree in Physics (1977), a PhD degree in High-Energy Physics (1981) and a D.Sc. degree (2008) from the University of Durham. From 1981 to 1991 he worked as a researcher in the fields of high-energy nuclear physics and pattern recognition at the Rutherford-Appleton Laboratory (now the Central Research Laboratory of the Research Council). During this period, he also held adjunct teaching posts at the University of Surrey and at the Open University. In 1991, he moved to the University of York as a lecturer, and later on became a Professor of Computer Vision. From 2003 to 2008 Dr. Hancock was Chair of the Departmental Research Committee; he currently leads a group of some 25 faculty, research staff, and PhD students working in the areas of computer vision and pattern recognition. His main research interests focus on the use of optimization and probabilistic methods for high and intermediate level vision. He is also interested in the methodology of structural and statistical pattern recognition. He is currently working on graph matching, shape-from-X, image databases, and statistical learning theory. His work has found applications in areas such as radar terrain analysis, seismic section analysis, remote sensing, and medical imaging.
He has published about 135 journal papers and 500 refereed conference publications. He was awarded the Pattern Recognition Society medal in 1991 and an outstanding paper award in 1997 by the journal "Pattern Recognition". He has also received best paper prizes at CAIP 2001, ACCV 2002, ICPR 2006 and BMVC 2007. In 2009 he was awarded a Royal Society Wolfson Research Merit Award. In 1998, he became a fellow of the International Association for Pattern Recognition. He is also a fellow of the Institute of Physics, the Institute of Engineering and Technology, and the British Computer Society. He has been a member of the editorial boards of the journals IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition, Computer Vision and Image Understanding, and Image and Vision Computing. In 2006, he was appointed as the founding editor-in-chief of the IET Computer Vision Journal. He has been conference chair for BMVC 1994, Track Chair for ICPR 2004 and Area Chair at ECCV 2006 and CVPR 2008, and in 1997 established the EMMCVPR workshop series.