Classifying Sentences Using Induced Structure

In this article we will introduce a new approach (and several implementations) to the task of sentence classification, where pre-defined classes are assigned to sentences. This approach concentrates on structural information that is present in the sentences. This information is extracted using machine learning techniques and the patterns found are used to classify the sentences. The approach fits in between the existing machine learning and hand-crafting of regular expressions approaches, and it combines the best of both. The sequential information present in the sentences is used directly, classifiers can be generated automatically and the output and intermediate representations can be investigated and manually optimised if needed.

[1]  Mark T. Maybury,et al.  Advances in Automatic Text Summarization , 1999 .

[2]  Claire Grover,et al.  Sentence classification experiments for legal text summarisation , 2004 .

[3]  Marc Moens,et al.  Argumentative Classification of Extracted Sentences as a First Step Towards Flexible Abstracting , 1999 .

[4]  Philippe Flajolet,et al.  The analysis of hybrid trie structures , 1998, SODA '98.

[5]  Eric Brill,et al.  A Simple Rule-Based Part of Speech Tagger , 1992, HLT.

[6]  Proceedings of The Eleventh Text REtrieval Conference, TREC 2002, Gaithersburg, Maryland, USA, November 19-22, 2002 , 2002, TREC.

[7]  Barak A. Pearlmutter,et al.  Results of the Abbadingo One DFA Learning Competition and a New Evidence-Driven State Merging Algorithm , 1998, ICGI.

[8]  Luiz Augusto Sangoi Pizzato,et al.  Using a Trie-based Structure for Question Analysis , 2004, ALTA.

[9]  Marcel Worring,et al.  NIST Special Publication , 2005 .

[10]  Dell Zhang,et al.  Question classification using support vector machines , 2003, SIGIR.

[11]  Dominique Estival,et al.  Theoretical and Practical Experiences with Alignment-Based Learning , 2003 .

[12]  Menno van Zaanen,et al.  Bootstrapping structure into language : alignment-based learning , 2001, ArXiv.

[13]  Menno van Zaanen,et al.  Alignment-based learning versus emile: A comparison , 2001 .

[14]  Jeroen Geertzen,et al.  Grammatical Inference Using Suffix Trees , 2004, ICGI.

[15]  Dan Roth,et al.  Learning Question Classifiers , 2002, COLING.