Call for Papers: The first workshop on Deep Matching in Practical Applications (DAPA 2019)
This workshop is a forum for exchanging ideas and methods about the challenges in applying deep matching models in real information retrieval scenarios as well as the theory behind the models and applications. The goal is to bring together researchers from both academia and industry, to provide an opportunity for people to present new work and early results, and discuss the main challenges in designing and applying deep matching models in practice. To reflect the broad scope of work on deep matching in practical application, we encourage submissions that span the spectrum from theoretical analysis to algorithms and implementation, to applications and empirical studies is various domains. Topics of interest include, but are not limited to: - Efficiency: Improving the efficiency of online inference for the deep neural network based matching models in large-scale distributed IR systems. - Generalizability: Understanding the generalizability of deep matching models, not only on public benchmark datasets, but also on real data traffic from real production systems. - Evaluation: Evaluating deep matching models with complicated metrics and targets (e.g., correctness, time complexity, and space complexity) in practical applications. - Interpretability: Interpreting the results of the deep matching models, as well as understanding the underlying mechanism in the models. - Connection: Uncovering the connection between deep matching models and classical IR approaches, the effect of different network components, and the benefits or risk they bring to production systems. - Robustness: Testing the robustness of deep matching models with respect to noise, bias, and imbalance distributions in data collected from practical applications. - Understanding: Understanding the fundamental differences between different matching problems (e.g., query-document matching in search, question-answer matching in QA) as well as the change of model behavior when applying deep matching techniques on them. All papers will be peer reviewed, single-blinded. We welcome many kinds of papers, such as, but not limited to: - Novel research papers - Demo papers - Work-in-progress papers - Visionary papers (white papers) - Appraisal papers of existing methods and tools (e.g., lessons learned) - Relevant work that has been previously published - Work that will be presented at the main conference of WSDM Authors should clearly indicate in their abstracts the kinds of submissions that the papers belong to, to help reviewers better understand their contributions. Submissions must be in PDF, no more than 6 pages long — shorter papers are welcome — and formatted according to the standard double-column ACM Proceedings Style <http://www.acm.org/publications/proceedings-template#aL2> . Key Dates - November 10, 2018: Submission deadline. - November 25, 2018: Accepted notification. - December 10, 2018: Camera ready version of accepted papers due. - February 15, 2019: DAPA workshop. All deadlines are 11:59pm, anywhere in the world (Alofi time <http://www.timeanddate.com/worldclock/city.html?n=724>). The accepted papers will be published on the workshop’s website and will not be considered archival for resubmission purposes. Authors whose papers are accepted to the workshop will have the opportunity to participate in a spotlight and poster session, and some set may also be chosen for oral presentation. For paper submission, please proceed to the submission website <https://easychair.org/conferences/?conf=dapa2019>. Yixing Fan, Institute of Computing Technology, CAS Qingyao Ai, CICS, UMass Amherst Zhaochun Ren, JD.com Dawei Yin, JD.com Jiafeng Guo, Institute of Computing Technology, CAS Email: [email protected]
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