Title :
Semantic role based sentence compression
Author :
Pourgholamali, Fatemeh ; Kahani, Mohsen
Author_Institution :
Web Technol. Lab., Ferdowsi Univ. of Mashhad, Mashhad, Iran
Abstract :
In this paper, a new unsupervised sentence compression method is proposed. Sentences are tagged with Part Of Speech tags and semantic role labels. The proposed method relies on the semantic roles of sentences´ parts. Moreover, in the process of compression, other sentences in the context are taken into account. The approach is applied in the context of multi-document summarization. Experiments showed better results than other state of the art approaches.
Keywords :
data compression; document handling; multidocument summarization; part-of-speech tag; semantic role based sentence compression; unsupervised sentence compression method; Barium; Context; Feature extraction; Grammar; Measurement; Semantics; Speech; Multi-Document Summarization; Part Of Speech; ROUGE; Semantic Role; Sentence Compression;
Conference_Titel :
Computer and Knowledge Engineering (ICCKE), 2012 2nd International eConference on
Conference_Location :
Mashhad
Print_ISBN :
978-1-4673-4475-3
DOI :
10.1109/ICCKE.2012.6395380
