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TopDozens of systems have been introduced for sentence compression and most of them are deletion based that heavily relies on syntactic information to minimize grammatical error in the output but that leads to a very complex system. Generally the sentence compression system used as a module in text summarization system so it is required that the compression system should be simple otherwise the overall complexity of the system will be very high.
Different sentence compression systems have been proposed by different researchers since its very fitst approach by Grefenstette (1998), Knight & Marcu (2000, 2002), Jing & McKeown (2000). Parsers play an important role in NLP task. Some sentence compression methods highly depend on parsers to identify syntactic information for sentence compression task Clarke & Lapata (2006), McDonald (2006), Toutanova, Brockett, Gamon, Jagarlamundi, Suzuki and Vanderwende (2007), Nomoto (2009), but systems based on syntactic information is not robust.
To produce grammatically correct compressed sentence some methods play with the syntactic structure of the tree Galley & McKeown (2007), Cohn & Lapata (2009), Filippova & Strube (2008a), Galanis & Androutsopoulos (2010), Wang, Raghavan, Castelli, Florian & Cardie (2013) use techniques that modify/rectify the syntactic trees.