Paper Info
Title
Match²: A Matching over Matching Model for Similar Question Identification
Abstract
Community Question Answering (CQA) has become a primary means for people to acquire knowledge, where people are free to ask questions or submit answers. To enhance the efficiency of the service, similar question identification becomes a core task in CQA which aims to find a similar question from the archived repository whenever a new question is asked. However, it has long been a challenge to properly measure the similarity between two questions due to the inherent variation of natural language, i.e., there could be different ways to ask a same question or different questions sharing similar expressions. To alleviate this problem, it is natural to involve the existing answers for the enrichment of the archived questions. Traditional methods typically take aone-side usage, which leverages the answer as some expanded representation of the corresponding question. Unfortunately, this may introduce unexpected noises into the similarity computation since answers are often long and diverse, leading to inferior performance. In this work, we propose atwo-side usage, which leverages the answer as a bridge of the two questions. The key idea is based on our observation that similar questions could be addressed by similar parts of the answer while different questions may not. In other words, we can compare the matching patterns of the two questions over the same answer to measure their similarity. In this way, we propose a novel matching over matching model, namely Match2, which compares the matching patterns between two question-answer pairs for similar question identification. Empirical experiments on two benchmark datasets demonstrate that our model can significantly outperform previous state-of-the-art methods on the similar question identification task.
Year
DOI
Venue
2020
10.1145/3397271.3401143
SIGIR '20: The 43rd International ACM SIGIR conference on research and development in Information Retrieval Virtual Event China July, 2020
DocType
ISBN
Citations 
Conference
978-1-4503-8016-4
2
PageRank 
References 
Authors
0.35
0
9
Name
Order
Citations
PageRank
Zizhen Wang122.04
Yixing Fan220219.39
Jiafeng Guo31737102.17
Liu Yang438018.54
Ruqing Zhang51510.40
Yanyan Lan6100563.59
Xueqi Cheng73148247.04
Hui Jiang884.32
Xiaozhao Wang920.35