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Lifebrowser looks for clues about whether a file is especially significant, and asks for extra hints if it’s unsure. A screen saver prompts a user to inform Lifebrowser if certain photos are of “landmark” events or not, and a simple dialogue does the same for calendar invitations. Over time, the system learns what’s important to you, and adapts. “You always think that machine learning is kind of cold,” says Horvitz. “This is showing that a model is not only learning about how I think, it’s also very warmly understanding what it means to capture humanity.”

Lifebrowser is impressive, says Sudheendra Hangal, a researcher at Stanford University who has built a tool called Muse (try it here) that helps people explore their e-mail archives with visualizations and other tools. Hangal has seen only a video of Horvitz’s software.

Hangal says trials of Muse have shown that most people are very interested in exploring their digital past if they have tools that make it easy. One popular use case is for people to find old e-mails and forward them to the original recipient to reminisce; another use is to look back and rediscover significant personal events.

Lifebrowser could let people do those things with more than just their e-mail, but Hangal suggests that systems like Lifebrowser and Muse could be most useful if they’re used to personalize other software and Web services. “Imagine if all the software on your machine could have access to this information,” says Hangal. “Because it reflects what you have done for many years, it offers very good personalization but is privacy-preserving.” That approach would be very different from the kind of data-mining-based personalization most common today, where companies such as Google or Facebook tailor content based upon the relatively short trail of personal data available to them.

Horvitz says he is considering how Lifebrowser’s knowledge could be used that way. “There’s a lot of possibility for data mining and personalization in the privacy of your own machine,” he says. “I would not feel comfortable sharing all this with a cloud service.”

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Credit: Microsoft Research

Tagged: Computing, Facebook, data mining, machine learning, Microsoft Research

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