Social Lead Identification Year Two

Millions of people post information on social media sites about their interests, preferences, opinions etc. on a daily basis. LeadSift mines this data stream in real-time to generate incredibly accurate and targeted sales leads. Given the short text and ambiguity around a social post, it gets very difficult to accurately identify intent. This project will explore different Natural Language Processing techniques to analyze the inherent semantic structure of social posts. Due the real-time nature of the social data, the algorithms need to be extremely efficient and scalable. The expected benefit to LeadSift will be dramatic improvement in the quality of the sales leads we can generate from socia media

Faculty Supervisor:

Vlado Keselj

Student:

Partner:

LeadSift

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Dalhousie University

Program: