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The HKUST team, consisting of D. Shen, R. Pan, J.T. Sun, J.F. Pan, K.H. Wu, J. Yin, and Professor Q. Yang, achieved a remarkable feat by winning all three awards at the ACM KDD Cup 2005: Query Categorization Precision, Query Categorization Performance, and Query Categorization Creativity. Faced with the challenge of categorizing 800,000 ambiguous queries into 67 predefined categories without training data, their innovative approach navigated the complexities of query meanings and semantics to deliver superior results, showcasing their excellence in data science.
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HKUST won all three awards for KDDCup 2005: Query Categorization Precision Award, Query Categorization Performance Award Query Categorization Creativity Award ACM KDD-CUP 2005HKUST Team: D. Shen, R. Pan, J.T. Sun, J.F. Pan, K.H. Wu, J. Yin and Professor Q. Yang • Key Characteristics: • No training data • Meaning of Queries: ambiguous • A query usually contains too few words; • Queries often have more than one meaning. • Semantics of Categories: uncertain • Only the names of Categories, no more specification; • Task • Categorize 800,000 queries into 67 predefined categories; • Limitation • “There is no restriction on what data you can/can't use to build your models.” From http://kdd05.lac.uic.edu/kddcup.html Phase I Phase II Ensemble
