@inproceedings{Molla:2006b,
  abstract = {In this paper we present a graph-based approach to question answering. The method assumes a graph representation of question sentences and text sentences. Question answering rules are automatically learnt from a training corpus of questions and answer sentences with the answer annotated. The method is independent from the graph representation formalism chosen. A particular example is presented that uses a specific graph representation of the logical contents of sentences.},
  added-at = {2008-02-06T06:48:51.000+0100},
  author = {Moll\'{a}, Diego},
  biburl = {http://www.bibsonomy.org/bibtex/2d40066e489bb1545f2afc538c451b0b3/diego_ma},
  booktitle = {Proc. HLT/NAACL 2006 Workshop on Graph Algorithms for Natural Language Processing},
  interhash = {519694cc699f9f82a8a2cf0d56e6d0f4},
  intrahash = {d40066e489bb1545f2afc538c451b0b3},
  keywords = {graphs AnswerFinder molla_publication},
  pages = {37-44},
  timestamp = {2008-02-06T06:48:51.000+0100},
  title = {Learning of Graph-based Question Answering Rules},
  url = {http://www.ics.mq.edu.au/~diego/publications/NAACL06Graphs.pdf},
  year = 2006
}