| |
Modelling Domain Relationships for Transfer Learning on Retrieval-based Question Answering Systems in E-commerce
Speaker (s):
Yu Jianfei
PhD Candidate
School of Information Systems
Singapore Management University
|
|
Date:
Time:
Venue:
|
|
February 2, 2018, Friday
9:30am - 10:00am
Meeting Room 4.4, Level 4
School of Information Systems
Singapore Management University
80 Stamford Road
Singapore 178902
We look forward to seeing you at this research seminar.
|
|
About the Talk
Nowadays, it is a heated topic for many industries to build automatic question-answering (QA) systems. A key solution to these QA systems is to retrieve from a QA knowledge base the most similar question of a given question, which can be reformulated as a paraphrase identification (PI) or a natural language inference (NLI) problem. However, most existing models for PI and NLI have at least two problems: They rely on a large amount of labeled data, which is not always available in real scenarios, and they may not be efficient for industrial applications.
In this paper, we study transfer learning for the PI and NLI problems, aiming to propose a general framework, which can effectively and efficiently adapt the shared knowledge learned from a resource-rich source domain to a resource-poor target domain. Specifically, since most existing transfer learning methods only focus on learning a shared feature space across domains while ignoring the relationship between the source and target domains, we propose to simultaneously learn shared representations and domain relationships in a unified framework. Furthermore, we propose an efficient and effective hybrid model by combining a sentence encoding-based method and a sentence interaction-based method as our base model. Extensive experiments on both paraphrase identification and natural language inference demonstrate that our base model is efficient and has promising performance compared to the competing models, and our transfer learning method can help to significantly boost the performance. Further analysis shows that the inter-domain and intra-domain relationship captured by our model are insightful. Last but not least, we deploy our transfer learning model for PI into AliExpress’s online chatbot system, which can bring in significant improvements over their existing system.
Finally, we launch our new system on the chatbot platform Eva in Alibaba’s real E-commerce site AliExpress.
This a pre-conference talk for the 11th ACM International Conference on Web Search and Data Mining (WSDM 2018).
About the Speaker
YU Jianfei is a PhD candidate in the School of Information Systems, Singapore Management University, under the supervision of Associate Prof. Jing Jiang. He received his Bachelor and Master degree from Nanjing University of Science and Technology, China in 2012 and 2015 respectively. Currently, he works in the area of text mining with a focus on applying deep learning and transfer learning techniques to some NLP tasks like Question Answering, Relation Extraction, Sentiment Analysis, etc.
|
