logo
banner

Journals & Publications

Journals Publications Papers

Papers

Comparison Study on Critical Components in Composition Model for Phrase Representation
Jul 24, 2017Author:
PrintText Size A A

Title: Comparison Study on Critical Components in Composition Model for Phrase Representation

 Authors: Wang, SN; Zong, CQ

 Author Full Names: Wang, Shaonan; Zong, Chengqing

 Source: ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING, 16 (3):10.1145/3010088 APR 2017

 Language: English

 Abstract: Phrase representation, an important step in many NLP tasks, involves representing phrases as continuousvalued vectors. This article presents detailed comparisons concerning the effects of word vectors, training data, and the composition and objective function used in a composition model for phrase representation. Specifically, we first discuss how the augmented word representations affect the performance of the composition model. Then, we investigate whether different types of training data influence the performance of the composition model and, if so, how they influence it. Finally, we evaluate combinations of different composition and objective functions and discuss the factors related to composition model performance. All evaluations were conducted in both English and Chinese. Our main findings are as follows: (1) The Additive model with semantic enhanced word vectors performs comparably to the state-of-the-art model; (2) The Additive model which updates augmented word vectors and the Matrix model with semantic enhanced word vectors systematically outperforms the state-of-the-art model in bigram and multi-word phrase similarity task, respectively; (3) Representing the high frequency phrases by estimating their surrounding contexts is a good training objective for bigram phrase similarity tasks; and (4) The performance gain of composition model with semantic enhanced word vectors is due to the composition function and the greater weight attached to important words. Previous works focus on the composition function; however, our findings indicate that other components in the composition model (especially word representation) make a critical difference in phrase representation.

 ISSN: 2375-4699

 eISSN: 2375-4702

 Article Number: 16

 IDS Number: ER8QW

 Unique ID: WOS:000399087800002

*Click Here to View Full Record