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XMLC for SocMed 2018 : Extreme Multilabel Classification for Social Media In association with The Web Conference 2018, Lyon, France | |||||||||||||||
Link: https://sites.google.com/view/xmlc/ | |||||||||||||||
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Call For Papers | |||||||||||||||
24 April, 2018
Extreme Multilabel Classification for Social Media In association with The Web Conference 2018, Lyon, France https://sites.google.com/view/xmlc/ The Web Conference showcases state-of-the-art research in the fields of information retrieval, machine learning, artificial intelligence and computer science in general. The theme of this workshop is Extreme Multilabel Classification (XMLC). XMLC is a very active and rapidly growing research area that deals with the problem of labeling an item with a set of tags out of an extremely large number of potential tags. While the difficulty and the potential applications of XMLC are well understood in the core machine learning community, to the best of our knowledge, XMLC has not made inroads in the field of Information Retrieval (IR) and related areas. The aim of this workshop is to bring researchers from academia and industry to further advance this very exciting field and come up with potential applications of XMLC in new areas. Authors are invited to submit long (8 pages) and short (4 pages) papers, please clicks the following link for submission: https://easychair.org/conferences/?conf=www2018satellites Topics of interest include: Given that the main aim of this workshop is to identify new application areas for XMLC, we propose topics that are aligned with this goal along with other topics in this area: New applications of XMLC: social media events, hashtags detection e.g., Twitter moments, e-commerce, multi-lingual XMLC Structured XMLC: knowledge graph/taxonomy, events as labels: temporally structured events, spatially similar events Incremental inclusion of new labels and training data: zero shot learning, pre- and post-training, active learning Multi-task multilabel learning: transfer learning, semi-supervised learning Computational aspects of XMLC: log-time and log-space prediction, model and computation parallelization Bayesian models for XMLC: generative models for XMLC, tackling label polysemy, synonymy and correlations. Deep XMLC: neural models for XMLC Evaluation for XMLC: novel metrics for XMLC evaluation Feature extraction and feature engineering for XMLC Important Dates Submission Deadline: 10 February 2018 Acceptance Notification: 25 February 2018 Final Version Due: 4 March 2018 Workshop Date: 24 April 2018 Organizing Committee: Akshay Soni, Yahoo Research, Sunnyvale Robert Busa-Fekete, Yahoo Research, New York Krzysztof Dembczyński, Poznan University of Technology Aasish Pappu, Yahoo Research, New York |
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