Paper: Unsupervised Natural Language Processing Using Graph Models

ACL ID N07-3010
Title Unsupervised Natural Language Processing Using Graph Models
Venue Human Language Technologies
Session Doctoral Consortium
Year 2007

In the past, NLP has always been based on the explicit or implicit use of linguistic knowledge. In classical computer linguis- tic applications explicit rule based ap- proaches prevail, while machine learning algorithms use implicit knowledge for generating linguistic knowledge. The question behind this work is: how far can we go in NLP without assuming explicit or implicit linguistic knowledge? How much efforts in annotation and resource building are needed for what level of so- phistication in text processing? This work tries to answer the question by experi- menting with algorithms that do not pre- sume any linguistic knowledge in the system. The claim is that the knowledge needed can largely be acquired by know- ledge-free and unsupervised methods. Here, graph models are employed for r...