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Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Tasks.

, , , , , , and . KDD, page 596-605. ACM, (2018)

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Learning to Identify Students' Off-Task Behavior in Intelligent Tutoring Systems., , , , and . AIED, volume 200 of Frontiers in Artificial Intelligence and Applications, page 701-703. IOS Press, (2009)Cross-domain and cross-category emotion tagging for comments of online news., , , , , and . SIGIR, page 627-636. ACM, (2014)Effect of varying number of documents in blind feedback: analysis of the 2003 NRRC RIA workshop "bf_numdocs" experiment suite., , , and . SIGIR, page 476-477. ACM, (2004)StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding., , , , , , , and . ICLR, OpenReview.net, (2020)A robust one-class bayesian approach for masquerade detection., and . AISec, page 111-112. ACM, (2011)Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Tasks., , , , , , and . KDD, page 596-605. ACM, (2018)Mixture model with multiple centralized retrieval algorithms for result merging in federated search., and . SIGIR, page 821-830. ACM, (2012)Learning compact hashing codes for efficient tag completion and prediction., , , and . CIKM, page 1789-1794. ACM, (2013)Unified utility maximization framework for resource selection., and . CIKM, page 32-41. ACM, (2004)The Effect of Database Size Distribution on Resource Selection Algorithms., and . Distributed Multimedia Information Retrieval, volume 2924 of Lecture Notes in Computer Science, page 31-42. Springer, (2003)