Contextual Suggestion

User profiling is essential in contextual suggestion. However, given most users’ observed behaviors are sparse and their preferences are latent in an IR system, constructing accurate user profiles is generally difficult. We focus on location-based contextual suggestion and propose to leverage users’ opinions to construct the profiles and thus significantly improve the system over category or description based user profile modeling approaches.

Achievements:

• Top 3 Performance on Contextual Suggestion track of the Text REtrieval Conference(TREC), 2015
• Top 1 Performance on Contextual Suggestion track of the Text REtrieval Conference(TREC), 2014
• Top 1 Performance on Contextual Suggestion track of the Text REtrieval Conference(TREC), 2013
• Top 3 Performance on Contextual Suggestion track of the Text REtrieval Conference(TREC), 2012

Skills: LAMP Stack, Standford NLP Packages, sciklearn