What is it about?

Have you ever heard that many computer system projects end up failing? Over half of them do! We wanted to know why. Think of a computer system project as a complex puzzle. We tried using machine learning – a type of smart computer analysis – to dig through a mountain of scattered puzzle pieces (data) from these projects to find patterns. And guess what? We found 4 main reasons these projects fail by analyzing tons of data. Now, with these insights, we can hopefully prevent such failures in the future.

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Why is it important?

Many have talked about the frequent failures in computer system projects, but few have used the advanced tool of machine learning to pinpoint the exact reasons. Our research is like a detective using a new kind of magnifying glass to spot clues missed by others. Considering the rise in the number of such projects worldwide, our findings can be a game-changer, helping teams and companies avoid common pitfalls.

Perspectives

Diving deep into this research was like embarking on a treasure hunt for me. I've always been intrigued by the challenges faced in computer system projects, and to find tangible reasons for their failures using machine learning was immensely satisfying. It's my hope that this work will not only shed light on these challenges but also inspire a new way of approaching and solving complex problems in the tech world.

Assoc. Prof. Narasimha Rao Vajjhala
University of New York at Tirana

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This page is a summary of: Applying machine learning methods to understand unstructured information system big data, June 2022, Institute of Electrical & Electronics Engineers (IEEE),
DOI: 10.23919/cisti54924.2022.9820116.
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