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MACHINE LEARNING
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About |
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Recommendation systems are used widely in eCommerce industries and multimedia content platforms to provide suggestions that a user will most likely consume; thus, improving the user experience. This motivates people in both industry and research organizations to focus on personalization or recommendation algorithms, which has resulted in a plethora of research papers. While academic research mostly focuses on the performance of recommendation algorithms in terms of ranking quality or accuracy, it often neglects key factors that impact how a recommendation system will perform in a real-world environment. These key factors include but are not limited to: data and model scalability, model serving latency, model interpretability, and resource limitations, such as budget on compute and memory resources, engineering workforce cost, etc. The gap in constraints and requirements between academic research and industry limits the broad applicability of many of academia’s contributions for industrial recommendation systems. This workshop aspires to bridge this gap by bringing together researchers from both academia and industry. Its goal is to serve as a platform via which academic researchers become aware of the additional factors that may affect the chances of algorithm adoption into real production systems, and the performance of the algorithms if deployed. Industrial researchers will also benefit from sharing the practical frameworks at an industrial level. |
Call for Papers |
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This workshop welcomes submissions from researchers and industrial practitioners broadly related to recommendation systems, such as novel recommendation models, efficient recommendation algorithms, novel industrial frameworks, etc. In order to emphasize the gap between the two communities, we extremely welcome submissions on industrial recommendation system infrastructures based on given resources, models and algorithms supported by the specific infrastructures, and frameworks or end-to-end systems that have been deployed in real world production. Specific topics of interest are including but not limited to:
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Summary |
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IRS 2020 : 1st International Workshop on Industrial Recommendation Systems will take place in San Diego, CA. It’s a 1 day event starting on Aug 24, 2020 (Monday) and will be winded up on Aug 24, 2020 (Monday). IRS 2020 falls under the following areas: MACHINE LEARNING, etc. Submissions for this Workshop can be made by May 20, 2020. Authors can expect the result of submission by Jun 15, 2020. Please check the official event website for possible changes before you make any travelling arrangements. Generally, events are strict with their deadlines. It is advisable to check the official website for all the deadlines. Other Details of the IRS 2020
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Credits and Sources |
| [1] IRS 2020 : 1st International Workshop on Industrial Recommendation Systems |
