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Scalable Hybrid Machine Learning Framework for Interpretable Anomaly Detection in Distributed Server Logs.

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Title: Scalable Hybrid Machine Learning Framework for Interpretable Anomaly Detection in Distributed Server Logs.
Authors: B., Bizu1, bizucse@gmail.com, K., Suvalakshmi1, suva1798@gmail.com, C., Roopa1, roopavivin@gmail.com, R., Ahalya1, ahalya.r2004@gmail.com, P. L., Bairavi1, bairavi2407@gmail.com, S., Gobika1, gobika011@gmail.com
Source: Grenze International Journal of Engineering & Technology (GIJET); Jan2026, Vol. 12 Issue Part2, p2879-2887, 9p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
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PubType: Academic Journal
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  Data: Scalable Hybrid Machine Learning Framework for Interpretable Anomaly Detection in Distributed Server Logs.
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      – Code: eng
        Text: English
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        PageCount: 9
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      – TitleFull: Scalable Hybrid Machine Learning Framework for Interpretable Anomaly Detection in Distributed Server Logs.
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            NameFull: B., Bizu
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              M: 01
              Text: Jan2026
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              Y: 2026
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