Methods for Sentence Compression

Sentence compression is the task of producing a summary of a single sentence. The compressed sentence should be shorter, contain the important content from the original, and itself be grammatical. The three papers discussed here take different approaches to identifying important content, determining which sentences are grammatical, and jointly optimizing these objectives. One family of approaches we will discuss is those that are tree-based, which create a compressed sentence by making edits to the syntactic tree of the original sentence. A second type of approach is sentence-based, which generates strings directly. Orthogonal to either of these two approaches is whether sentences are treated in isolation or if the surrounding discourse affects compressions. We compare a tree-based, a sentence-based, and a discourse-based approach and conclude with ideas for future work in this area. Comments University of Pennsylvania Department of Computer and Information Science Technical Report No. MSCIS-10-20. This technical report is available at ScholarlyCommons: http://repository.upenn.edu/cis_reports/929 Methods for Sentence Compression

[1]  Daniel Marcu,et al.  A Noisy-Channel Model for Document Compression , 2002, ACL.

[2]  Koby Crammer,et al.  Ultraconservative Online Algorithms for Multiclass Problems , 2001, J. Mach. Learn. Res..

[3]  Kaizhong Zhang,et al.  Simple Fast Algorithms for the Editing Distance Between Trees and Related Problems , 1989, SIAM J. Comput..

[4]  Stefan Riezler,et al.  Statistical Sentence Condensation using Ambiguity Packing and Stochastic Disambiguation Methods for Lexical-Functional Grammar , 2003, NAACL.

[5]  Chin-Yew Lin Improving summarization performance by sentence compression: a pilot study , 2003, IRAL.

[6]  Ryan T. McDonald Discriminative Sentence Compression with Soft Syntactic Evidence , 2006, EACL.

[7]  Koby Crammer,et al.  Online Large-Margin Training of Dependency Parsers , 2005, ACL.

[8]  Mirella Lapata,et al.  Models for Sentence Compression: A Comparison across Domains, Training Requirements and Evaluation Measures , 2006, ACL.

[9]  William B. Dolan,et al.  Less is more: Eliminating index terms from subordinate clauses , 1999, ACL.

[10]  Gregory Grefenstette Producing Intelligent Telegraphic Text Reduction to provide an Audio Scanning Service for the Blind , 1998 .

[11]  Ani Nenkova,et al.  References to Named Entities: a Corpus Study , 2003, HLT-NAACL.

[12]  David Chiang,et al.  An Introduction to Synchronous Grammars , 2006 .

[13]  Peter Norvig,et al.  The Unreasonable Effectiveness of Data , 2009, IEEE Intelligent Systems.

[14]  Michael Collins,et al.  Head-Driven Statistical Models for Natural Language Parsing , 2003, CL.

[15]  Mirella Lapata,et al.  Large Margin Synchronous Generation and its Application to Sentence Compression , 2007, EMNLP.

[16]  Regina Barzilay,et al.  Using Lexical Chains for Text Summarization , 1997 .

[17]  Beatrice Santorini,et al.  Building a Large Annotated Corpus of English: The Penn Treebank , 1993, CL.

[18]  Scott Weinstein,et al.  Centering: A Framework for Modeling the Local Coherence of Discourse , 1995, CL.

[19]  Mirella Lapata,et al.  Constraint-Based Sentence Compression: An Integer Programming Approach , 2006, ACL.

[20]  Kathleen McKeown,et al.  Lexicalized Markov Grammars for Sentence Compression , 2007, NAACL.

[21]  Kathleen F. McCoy,et al.  Efficiently Computed Lexical Chains as an Intermediate Representation for Automatic Text Summarization , 2002, CL.

[22]  Tadashi Nomoto A Comparison of Model Free versus Model Intensive Approaches to Sentence Compression , 2009, EMNLP.

[23]  Hongyan Jing,et al.  Sentence Reduction for Automatic Text Summarization , 2000, ANLP.

[24]  Mark Johnson,et al.  PCFG Models of Linguistic Tree Representations , 1998, CL.

[25]  J. Clarke,et al.  Global inference for sentence compression : an integer linear programming approach , 2008, J. Artif. Intell. Res..

[26]  Mirella Lapata,et al.  Modelling Compression with Discourse Constraints , 2007, EMNLP.

[27]  Aravind K. Joshi,et al.  Tree Adjunct Grammars , 1975, J. Comput. Syst. Sci..

[28]  Eugene Charniak,et al.  Supervised and Unsupervised Learning for Sentence Compression , 2005, ACL.

[29]  Alfred V. Aho,et al.  Syntax Directed Translations and the Pushdown Assembler , 1969, J. Comput. Syst. Sci..

[30]  Dan Klein,et al.  Accurate Unlexicalized Parsing , 2003, ACL.

[31]  Michael Halliday,et al.  Cohesion in English , 1976 .

[32]  Daniel Marcu,et al.  Summarization beyond sentence extraction: A probabilistic approach to sentence compression , 2002, Artif. Intell..

[33]  Mirella Lapata,et al.  Sentence Compression Beyond Word Deletion , 2008, COLING.

[34]  Tadashi Nomoto A Generic Sentence Trimmer with CRFs , 2008, ACL.

[35]  William C. Mann,et al.  Rhetorical Structure Theory: Toward a functional theory of text organization , 1988 .

[36]  Kathleen McKeown,et al.  Improving Word Sense Disambiguation in Lexical Chaining , 2003, IJCAI.

[37]  Sadaoki Furui,et al.  Speech Summarization: An Approach through Word Extraction and a Method for Evaluation , 2004, IEICE Trans. Inf. Syst..

[38]  Richard Edwin Stearns,et al.  Syntax-Directed Transduction , 1966, JACM.

[39]  Graeme Hirst,et al.  Lexical Cohesion Computed by Thesaural relations as an indicator of the structure of text , 1991, CL.