Building a conversational system is considered a hardcore research problem. To have such a system is a research interest as well as commercial interest of E-commerce companies especially nowadays, in the big data era. Most of the advanced models, mainly in the field of Deep Neural Networks, focus on response generation but still suffer from generic responses. In this work, we present novel methods for searching knowledge-grounded responses. Empirical evaluation demonstrates the effectiveness of these methods.