Title :
Recognition of Paraphrasing Pairs
Author_Institution :
Div. de Posgrado e Investig., Inst. Tecnol. de la Laguna, Mexico City
fDate :
Sept. 30 2008-Oct. 3 2008
Abstract :
Our approach to recognize paraphrasing pairs is to make use of lexical relationships as representations of paraphrases. In this paper, we describe a classification process based on logistic regression as the inference mechanism. In this way, the set of features to be analyzed correspond to dependency trees from semantically equivalent paraphrase pairs. The results of the experimentation conducted show how a model constructed around lexical relationships is a plausible alternative for paraphrasing detection.
Keywords :
inference mechanisms; natural language processing; regression analysis; classification; dependency trees; inference mechanism; lexical relationship; logistic regression; natural language processing; paraphrasing detection; paraphrasing pairs recognition; Automotive engineering; Data mining; Induction generators; Inference algorithms; Inference mechanisms; Information retrieval; Lattices; Logistics; Robots; Semisupervised learning; Paraphrasing; alignment; dependency tree; logistic regression;
Conference_Titel :
Electronics, Robotics and Automotive Mechanics Conference, 2008. CERMA '08
Conference_Location :
Morelos
Print_ISBN :
978-0-7695-3320-9
DOI :
10.1109/CERMA.2008.56
