Towards Knowledge-Based Personalized Product Description Generation in E-commerce

ABSTRACT

Quality product descriptions are critical for providing competitive customer experience in an E-commerce platform. An accurate and attractive description not only helps customers make an informed decision but also improves the likelihood of purchase. However, crafting a successful product description is tedious and highly time-consuming. Due to its importance, automating the product description generation has attracted considerable interest from both research and industrial communities. Existing methods mainly use templates or statistical methods, and their performance could be rather limited. In this paper, we explore a new way to generate personalized product descriptions by combining the power of neural networks and knowledge base. Specifically, we propose a KnOwledge Based pErsonalized (or KOBE) product description generation model in the context of E-commerce.

In KOBE, we extend the encoder-decoder framework, the Transformer, to a sequence modeling formulation using self-attention. In order to make the description both informative and personalized, KOBE considers a variety of important factors during text generation, including product aspects, user categories, and knowledge base. Experiments on real-world datasets demonstrate that the proposed method outperforms the baseline on various metrics. KOBE can achieve an improvement of 9.7% over state-of-the-arts in terms of BLEU. We also present several case studies as the anecdotal evidence to further prove the effectiveness of the proposed approach. The framework has been deployed in Taobao, the largest online E-commerce platform in China.

References

1. Nabiha Asghar, Pascal Poupart, Jesse Hoey, Xin Jiang, and Lili Mou. 2018. Affective Neural Response Generation. In ECIR'18. Springer, 154--166.
2. Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 (2014).
3. Antoine Bordes, Y-Lan Boureau, and Jason Weston. 2016. Learning end-to-end goal-oriented dialog. arXiv preprint arXiv:1605.07683 (2016).
4. Sumit Chopra, Michael Auli, and Alexander M. Rush. 2016. Abstractive Sentence Summarization with Attentive Recurrent Neural Networks. In NAACL'16 . 93--98.
5. Konstantina Christakopoulou, Alex Beutel, Rui Li, Sagar Jain, and Ed H. Chi. 2018. Q&R: A Two-Stage Approach Toward Interactive Recommendation. In KDD'18 . 139--148.
6. Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018).
7. Jessica Ficler and Yoav Goldberg. 2017. Controlling Linguistic Style Aspects in Neural Language Generation. In Proceedings of the Workshop on Stylistic Variation. 94--104.
8. Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, and Yann N. Dauphin. 2017. Convolutional Sequence to Sequence Learning. In ICML'17. 1243--1252.
9. Shima Gerani, Yashar Mehdad, Giuseppe Carenini, Raymond T Ng, and Bita Nejat. 2014. Abstractive summarization of product reviews using discourse structure. In Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP) . 1602--1613.
10. Marjan Ghazvininejad, Chris Brockett, Ming-Wei Chang, Bill Dolan, Jianfeng Gao, Wen-tau Yih, and Michel Galley. 2017. A Knowledge-Grounded Neural Conversation Model. (2017). arxiv: 1702.01932 http://arxiv.org/abs/1702.01932
11. Jonathan Herzig, Michal Shmueli-Scheuer, Tommy Sandbank, and David Konopnicki. 2017. Neural response generation for customer service based on personality traits. In INLG'17 . 252--256.
12. Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, and Eric P Xing. 2017. Toward controlled generation of text. arXiv preprint arXiv:1703.00955 (2017).
13. Armand Joulin, Edouard Grave, Piotr Bojanowski, and Tomas Mikolov. 2016. Bag of tricks for efficient text classification. arXiv preprint arXiv:1607.01759 (2016).
14. Yoon Kim. 2014. Convolutional neural networks for sentence classification. arXiv preprint arXiv:1408.5882 (2014).
15. Diederik P Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014).
16. Guillaume Lample, Sandeep Subramanian, Eric Smith, Ludovic Denoyer, Marc'Aurelio Ranzato, and Y-Lan Boureau. 2019. Multiple-Attribute Text Rewriting. In ICLR'19 . https://openreview.net/forum?id=H1g2NhC5KQ
17. Irene Langkilde and Kevin Knight. 1998. Generation that exploits corpus-based statistical knowledge. In ACL'98. Association for Computational Linguistics, 704--710.
18. Jiwei Li, Michel Galley, Chris Brockett, Georgios Spithourakis, Jianfeng Gao, and Bill Dolan. 2016a. A Persona-Based Neural Conversation Model. In ACL'16, Vol. 1. 994--1003.
19. Jiwei Li, Will Monroe, Alan Ritter, Dan Jurafsky, Michel Galley, and Jianfeng Gao. 2016b. Deep Reinforcement Learning for Dialogue Generation. In EMNLP'16 . 1192--1202.
20. Jiwei Li, Will Monroe, Tianlin Shi, Sé bastien Jean, Alan Ritter, and Dan Jurafsky. 2017. Adversarial Learning for Neural Dialogue Generation. In EMNLP'17 . 2157--2169.
21. Zachary C Lipton, Sharad Vikram, and Julian McAuley. 2015. Capturing meaning in product reviews with character-level generative text models. arXiv preprint arXiv:1511.03683 (2015).
22. Thang Luong, Hieu Pham, and Christopher D. Manning. 2015. Effective Approaches to Attention-based Neural Machine Translation. In EMNLP'15 . 1412--1421.
23. Laurens van der Maaten and Geoffrey Hinton. 2008. Visualizing data using t-SNE. Journal of machine learning research , Vol. 9, Nov (2008), 2579--2605.
24. Paul Michel and Graham Neubig. 2018. Extreme Adaptation for Personalized Neural Machine Translation. arXiv preprint arXiv:1805.01817 (2018).
25. Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013. Distributed representations of words and phrases and their compositionality. In Advances in neural information processing systems. 3111--3119.
26. Vinod Nair and Geoffrey E. Hinton. 2010. Rectified Linear Units Improve Restricted Boltzmann Machines. In ICML'10. 807--814.
27. Ramesh Nallapati, Bowen Zhou, C'i cero Nogueira dos Santos, cC aglar Gü lcc ehre, and Bing Xiang. 2016. Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond. In CoNLL'16. 280--290.
28. Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002. Bleu: a Method for Automatic Evaluation of Machine Translation. In ACL'02 . 311--318.
29. Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer. 2017. Automatic differentiation in pytorch. (2017).
30. Alexander M. Rush, Sumit Chopra, and Jason Weston. 2015. A Neural Attention Model for Abstractive Sentence Summarization. In EMNLP'15 . 379--389.
31. Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016. Controlling politeness in neural machine translation via side constraints. In ACL'16 . 35--40.
32. Minjoon Seo, Aniruddha Kembhavi, Ali Farhadi, and Hannaneh Hajishirzi. 2016. Bidirectional attention flow for machine comprehension. arXiv preprint arXiv:1611.01603 (2016).
33. Iulian Vlad Serban, Tim Klinger, Gerald Tesauro, Kartik Talamadupula, Bowen Zhou, Yoshua Bengio, and Aaron C. Courville. 2017. Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation. In AAAI'17. 3288--3294.
34. Maosong Sun, Xinxiong Chen, Kaixu Zhang, Zhipeng Guo, and Zhiyuan Liu. 2016. Thulac: An efficient lexical analyzer for chinese . Technical Report. Tsinghua University.
35. Ilya Sutskever, Oriol Vinyals, and Quoc V. Le. 2014. Sequence to Sequence Learning with Neural Networks. In NIPS'14 . 3104--3112.
36. Jian Tang, Yifan Yang, Sam Carton, Ming Zhang, and Qiaozhu Mei. 2016. Context-aware natural language generation with recurrent neural networks. arXiv preprint arXiv:1611.09900 (2016).
37. Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017. Attention is All you Need. In NIPS'17. 6000--6010.
38. Oriol Vinyals and Quoc Le. 2015. A neural conversational model. arXiv preprint arXiv:1506.05869 (2015).
39. Jinpeng Wang, Yutai Hou, Jing Liu, Yunbo Cao, and Chin-Yew Lin. 2017. A Statistical Framework for Product Description Generation. In IJCNLP'17 , Vol. 2. 187--192.
40. Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, et almbox. 2016. Google's neural machine translation system: Bridging the gap between human and machine translation. arXiv preprint arXiv:1609.08144 (2016).
41. Bo Xu, Yong Xu, Jiaqing Liang, Chenhao Xie, Bin Liang, Wanyun Cui, and Yanghua Xiao. 2017. CN-DBpedia: A never-ending Chinese knowledge extraction system. In IEA/AIE'19. Springer, 428--438.

Index Terms

• Computing methodologies

  • Artificial intelligence

    • Natural language processing

      • Natural language generation

• Information systems

  • Information retrieval

    • Retrieval tasks and goals

      • Recommender systems

  • Information systems applications

    • Data mining