PowerSet: Good For Searching Wikipedia!
There have been quite a few blogs today comparing the newly released preview of PowerSet (an alternative search engine) Vs. Google. The line we’ve been reading for a while now is that PowerSet uses NLP (Natural Language Processing) to figure out what you want to find, not just stuff that sort of has what you want to find in its body text.
Previous comparisons have been throwing out things like “what does an orange taste like?” or “what is the capital of New Zealand?” No one asks those kinds of questions. Therefore, I will just search “who is Hung Truong?” since I’m sure lots of people want to know. It’s probably the most popular search term of all time, really.
The Google search does pretty well. 6/10 links on the first page are actually attributable to me, Hung Truong (the most popular Hung Truong on Google today!).
Hmmm… Powerset just returns a bunch of stuff from Wikipedia. Unfortunately, I don’t have a Wikipedia article (yet)! 0/10 of the first 10 results are actually about me.
So there you have it. Google beats PowerSet because PowerSet is only good for searching Wikipedia at the moment. Usually, when I want to search Wikipedia, I use Wikipedia.
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Search for topics that are in Wikipedia and you’ll get a much better experience. You don’t even need to ask a question: just type in a topic name. Also, check out our enhanced Wikipedia pages that have tools for summarizing content.
Okay, PowerSet might serve well as a neat-o frontend for Wikipedia. But that qualify it as a search engine? Even after expanding the sources of content to many site won’t do much for finding anything in the “deep web” if you guys don’t have some kind of crawler. Maybe you do and you’re not returning results from it yet.
NLP might be suitable for searching something with extremely limited scope and uniform structure (Wikipedia articles), but the default Wikipedia search is already quite adept at finding what I want. Interesting idea, but still a long ways from being a definitive improvement over “keywordese”.