AliMe Assist: An Intelligent Assistant for Creating an Innovative E-commerce Experience

We present AliMe Assist, an intelligent assistant designed for creating an innovative online shopping experience in E-commerce. Based on question answering (QA), AliMe Assist offers assistance service, customer service, and chatting service. It is able to take voice and text input, incorporate context to QA, and support multi-round interaction. Currently, it serves millions of customer questions per day and is able to address 85% of them. In this paper, we demonstrate the system, present the underlying techniques, and share our experience in dealing with real-world QA in the E-commerce field.

[1]  Yoon Kim,et al.  Convolutional Neural Networks for Sentence Classification , 2014, EMNLP.

[2]  Zhoujun Li,et al.  DocChat: An Information Retrieval Approach for Chatbot Engines Using Unstructured Documents , 2016, ACL.

[3]  Rui Yan,et al.  Learning to Respond with Deep Neural Networks for Retrieval-Based Human-Computer Conversation System , 2016, SIGIR.

[4]  Quoc V. Le,et al.  Sequence to Sequence Learning with Neural Networks , 2014, NIPS.

[5]  Sanjay Ghemawat,et al.  MapReduce: Simplified Data Processing on Large Clusters , 2004, OSDI.

[6]  Quoc V. Le,et al.  A Neural Conversational Model , 2015, ArXiv.

[7]  David Vandyke,et al.  A Network-based End-to-End Trainable Task-oriented Dialogue System , 2016, EACL.

[8]  Wei Chu,et al.  AliMe Chat: A Sequence to Sequence and Rerank based Chatbot Engine , 2017, ACL.

[9]  Quoc V. Le,et al.  Distributed Representations of Sentences and Documents , 2014, ICML.

[10]  Tomas Mikolov,et al.  Enriching Word Vectors with Subword Information , 2016, TACL.

[11]  Yoshua Bengio,et al.  Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.

[12]  Matthew Henderson,et al.  Machine Learning for Dialog State Tracking: A Review , 2015 .

[13]  Zhoujun Li,et al.  Sequential Match Network: A New Architecture for Multi-turn Response Selection in Retrieval-based Chatbots , 2016, ArXiv.

[14]  Joelle Pineau,et al.  Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models , 2015, AAAI.

[15]  Xiang Li,et al.  Two are Better than One: An Ensemble of Retrieval- and Generation-Based Dialog Systems , 2016, ArXiv.