The nature of statistical learning theory
The nature of statistical learning theory
Learning in graphical models
HLT '01 Proceedings of the first international conference on Human language technology research
Shallow parsing on the basis of words only: a case study
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Learning in natural language: theory and algorithmic approaches
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
Memory-Based Language Processing (Studies in Natural Language Processing)
Memory-Based Language Processing (Studies in Natural Language Processing)
| Hi-index | 0.00 |
In this presentation, I will look back at 10 years of CoNLL conferences and the state of the art of machine learning of language that is evident from this decade of research. My conclusion, intended to provoke discussion, will be that we currently lack a clear motivation or "mission" to survive as a discipline. I will suggest that a new mission for the field could be found in a renewed interest for theoretical work (which learning algorithms have a bias that matches the properties of language?, what is the psycholinguistic relevance of learner design issues?), in more sophisticated comparative methodology, and in solving the problem of transfer, reusability, and adaptation of learned knowledge.