Sequential web user classification from system logs using BiLSTM and TCN
Researchers compared BiLSTM and TCN deep learning architectures for classifying web user behavior based on system log data. The study found both models achieved high accuracy in predicting user types without requiring personal data.
Why it matters
This research provides a privacy-preserving method for behavioral analytics in cloud platforms, improving how systems understand user intent without tracking individual identities.
Scientific Reports ( 2026 ) Cite this article
We’re sharing this article early to provide faster access to peer-reviewed, accepted research. It is citable and carries a permanent DOI. This version is subject to further edits and will be replaced automatically by the final Version of Record. All legal disclaimers apply.
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