March 25, 2024, 4:42 a.m. | Arnab Chakraborty, Vikas Raturi, Shrutendra Harsola

cs.LG updates on arXiv.org arxiv.org

arXiv:2203.16155v3 Announce Type: replace
Abstract: We consider the problem of developing a clickstream modeling framework for real-time customer event prediction problems in SaaS products like QBO. We develop a low-latency, cost-effective, and robust ensemble architecture (BBE-LSWCM), which combines both aggregated user behavior data from a longer historical window (e.g., over the last few weeks) as well as user activities over a short window in recent-past (e.g., in the current session). As compared to other baseline approaches, we demonstrate the superior …

abstract architecture arxiv behavior clickstream cost cs.lg customer data ensemble event framework latency low modeling prediction products real-time robust saas type

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