Natural Language Assistant: A Dialog System for Online Product Recommendation

With the emergence of e-commerce systems, successful information access on e-commerce websites becomes essential. Menu-driven navigation and keyword search currently provided by most commercial sites have considerable limitations, as they tend to overwhelm and frustrate users with lengthy, rigid and not very effective interactions. To provide an efficient solution for information access, we have built the Natural Language Assistant (NLA), a web-based natural language dialog system to help users find relevant products on e-commerce sites. The system brings together technologies in natural language processing and human computer interaction to create a faster and more intuitive way of interacting with web sites. By combining statistical parsing techniques with traditional AI rule-based technology, we have created a dialog system that accommodates both customer needs and business requirements. The system is currently embedded in an application for recommending laptops and was deployed as ...

• Type: Journal
• Year: 2002
• Where: AIM
• Authors: Joyce Yue Chai, Veronika Horvath, Nicolas Nicolov, Margo Stys, Nanda Kambhatla, Wlodek Zadrozny, Prem Melville
• Keywords: AIM 2002, AIM 2006, Information Access, Natural Language, Natural Language Dialog