Recommender systems are playing an increasingly important role
in e-commerce portals. Based on the massive data from JD.com, we are building
a novel recommendation model into the one of largest e-commerce platform with
the most advanced technologies in the industry. Our recommendation model has been
applied on the JD mall and JD app to help billions of JD users.
We are building the enterprise-class knowledge base to enhance JD’s
recommendation and search results with semantic-search knowledge gathered
from a wide variety of information sources. Our research directions for
knowledge graph at the Data Science Lab include:
DIALOGUE AND INTERACACTIVE SYSTEMS
WWe aim to build a data-driven virtual assistant or a chat companion
system with the aid of big data and deep learning techniques.
Information retrieval (IR) has been widely applied to lots of topics
in E-Commerce portals. The Data Science Lab focuses on the research that applies IR
technologies to enhance the performance of JD’s E-Commerce platform.
Our research topics for IR in E-Commerce includes:
NATURAL LANGUAGE PROCESSING
Natural language processing (NLP) technologies have been
widely applied into E-Commerce platforms. Based on the massive data from
our E-Commerce platform, the Data Science Lab @ JD.com is developing
state-of-the-art NLP to enterprise-level solutions to enhance the user
experience on JD.com. Our research directions for natural language processing includes:
Operations Research (OR) is the application of scientific
& mathematical methods to the study & analysis of problems involving complex
systems. We are improving the logistic systems of JD.com using OR methods such
as mathematical optimization and approximation algorithms.