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  According to Shah, the kind of star rating systems that are the status quo on the web today are flawed because, well, humans are flawed. "If my mood is bad today, I might give four stars, but tomorrow I'd give five stars. But if you ask me to compare two movies, most likely I will remain true to that for a while," Shah says in an article published this week on MIT's news site. "Your three stars might be my five stars, or vice versa. For that reason, I strongly believe that comparison is the right way to capture this." Of course, finding programmers is tough as it is, and not all web companies can afford to hire Apple-caliber software engineers or MIT Ph.D.s to formulate their recommendation engines. Also, users on sites such as Yelp have become very confident in their roles as armchair critics, adding and subtracting stars from reviews for highly specific reasons. But then again, classic websites such as HotorNot.com - and even Facebook predecessor FaceMash.com - have shown that one-to-one comparisons can be fun, too. According to the folks at MIT, if comparison engines can make the leap from fun pastime into the big leagues of e-commerce, recommendation systems could get even more spookily accurate.

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