Ask HN: Access to the Corpus - What Would You Do?
30 comments
So .. Google have these data. Their hacking chops are not unremarkable. What have they done with it? Well, basically, you can ask for a word and they'll find other pages that feature that word ...
And that's it.
They have access to "the world's combined knowledge" and a zillion PhDs, and that's all they can do?! It's shocking. But it's not, really, because the data are basically useless without annotations.
So let's go to Disneyland and pretend we have a genius NLP engine or an annotated web. Then,
1) 360 on a company/product. In particular: who are all the stakeholders, and how do they feel? I'd sell this to e.g. analysts. Same thing on people's online identities.
2) Memetracing. I'd sell this to advertisers. (So, we follow historical product releases and see exactly what memes spread about them and how, and through who. Related to (3) on ismarc's post)
3) Rumors (this would require your feed to be real-time). I'd also probably sell this to stock traders (the idea here is to monitor e.g. forums frequented by GE employees to guess scoop)
OK, so those are basic. More interesting:
4) Organization-tracing. If you can label social graph edges with influence levels / information intakes, you can start playing with predicting organizational decision-making (behavioral economics / game theory ..There's a TED talk about this).
5) Games: procedural content generation that looks really real, i.e. worlds full of people whose identities are plausible, whose interactions with others are plausible, etc.
Those all require some analytical / NLP firepower on a scale which I don't think is really doable at the moment. The problem is that bags of words are meaningless without a social context - the data are pretty worthless unless your computer can figure out who it's important for and why.
And that's it.
They have access to "the world's combined knowledge" and a zillion PhDs, and that's all they can do?! It's shocking. But it's not, really, because the data are basically useless without annotations.
So let's go to Disneyland and pretend we have a genius NLP engine or an annotated web. Then,
1) 360 on a company/product. In particular: who are all the stakeholders, and how do they feel? I'd sell this to e.g. analysts. Same thing on people's online identities.
2) Memetracing. I'd sell this to advertisers. (So, we follow historical product releases and see exactly what memes spread about them and how, and through who. Related to (3) on ismarc's post)
3) Rumors (this would require your feed to be real-time). I'd also probably sell this to stock traders (the idea here is to monitor e.g. forums frequented by GE employees to guess scoop)
OK, so those are basic. More interesting:
4) Organization-tracing. If you can label social graph edges with influence levels / information intakes, you can start playing with predicting organizational decision-making (behavioral economics / game theory ..There's a TED talk about this).
5) Games: procedural content generation that looks really real, i.e. worlds full of people whose identities are plausible, whose interactions with others are plausible, etc.
Those all require some analytical / NLP firepower on a scale which I don't think is really doable at the moment. The problem is that bags of words are meaningless without a social context - the data are pretty worthless unless your computer can figure out who it's important for and why.
"So .. Google have these data. Their hacking chops are not unremarkable. What have they done with it? Well, basically, you can ask for a word and they'll find other pages that feature that word ..."
There's actually a lot more that's done with it. Google Flu Trends. Google Zeitgeist. Google Squared. Google Suggest. Refinements. Spelling suggestions. Sitelinks. Wonder Wheel. Everything on Labs.
The limiting factor is more the ability to present the data to users without making them confused. It's pretty easy to run an analysis and get some data, but pretty difficult to figure "Okay, what problem does this solve?" and get that data in front of users in a way that actually solves the problem.
There's actually a lot more that's done with it. Google Flu Trends. Google Zeitgeist. Google Squared. Google Suggest. Refinements. Spelling suggestions. Sitelinks. Wonder Wheel. Everything on Labs.
The limiting factor is more the ability to present the data to users without making them confused. It's pretty easy to run an analysis and get some data, but pretty difficult to figure "Okay, what problem does this solve?" and get that data in front of users in a way that actually solves the problem.
If you really think that's all they're doing then you have very little understanding in just how subtly awesome some of the stuff they're doing is.
Peter Norvig does a better job explaining some of it than I ever could. http://www.youtube.com/watch?v=nU8DcBF-qo4
Peter Norvig does a better job explaining some of it than I ever could. http://www.youtube.com/watch?v=nU8DcBF-qo4
Peter Norvig says exactly what I said in that video.
He says it when he says "... but the computer doesn't understand physics." Why not? The internet knows a hell of a lot more physics than I do.
The statistical stuff is cool, but all you can do with it is fancy accounting. You can never really pull out meaning .. and doing real analogical / inductive reasoning on statistical data sets is hard.
You'll notice that suggestion (4) can only be considered doable because the internet has easily accessible APIs to determine who is real and what organizations they belong to.
While suggestion (5) is not feasible at all at the moment.
He says it when he says "... but the computer doesn't understand physics." Why not? The internet knows a hell of a lot more physics than I do.
The statistical stuff is cool, but all you can do with it is fancy accounting. You can never really pull out meaning .. and doing real analogical / inductive reasoning on statistical data sets is hard.
You'll notice that suggestion (4) can only be considered doable because the internet has easily accessible APIs to determine who is real and what organizations they belong to.
While suggestion (5) is not feasible at all at the moment.
SEO? With something like that you could programattically find semantic locations with lower coverage and then sell the knowledge that you could possibly attack that keyword. For instance, I'd love to see a chart which plotted frequency of use in an English corpus against some hypothetical Google-coverage variable. Anything that's a strong outlier from something like an exponential curve could be a good target.
I am not sure I understand in depth enough about SEO to fully understand this idea, but it sounds good in concept.
You have to consider that all that data isn't just a list of web pages. That includes information provided by the web page and the contents of the page itself (as well as associated metadata).
1) Create a map of the web (what links where and how), enabling an enhanced "browsing" experience (no more perusing a site for links to other interesting places)
2) The contents of those pages contain a large volume of technical documentation as well as a large number of opinions of the technologies that rose from the documentation. With both, and a large enough history of the creation of pages, the release of the documentation and the opinions presented, a model can be built to predict the success rate of any particular technology.
3) Given sufficient time, there is a large enough set of text that can be rendered to audio through speech synthesis (higher quality the better) in order to train a speech recognition system to a previously unseen level of accuracy.
4) Given a proper algorithm, sites with security vulnerabilities can be discovered just from what is crawlable and most likely should not be accessed. From that list, and given the total number of unique websites contained in the database, you can calculate the ratio of harmful to potentially non-harmful websites and provide a risk threshold of any given link on any given page.
5) Provide a search engine that uses regular expressions on different sets of the data (metadata, tags, text, text in a specific tag, etc.) to present a search engine with a previously unseen level of accuracy (accuracy of the results is dependent on the individual doing the searching, not the systems ability to guess that by std::list, I didn't mean "Sexually Transmitted Diseases STD List" (seriously, http://www.google.com/search?sourceid=chrome&ie=UTF-8... has that as the second result).
Edit: I failed at formatting
1) Create a map of the web (what links where and how), enabling an enhanced "browsing" experience (no more perusing a site for links to other interesting places)
2) The contents of those pages contain a large volume of technical documentation as well as a large number of opinions of the technologies that rose from the documentation. With both, and a large enough history of the creation of pages, the release of the documentation and the opinions presented, a model can be built to predict the success rate of any particular technology.
3) Given sufficient time, there is a large enough set of text that can be rendered to audio through speech synthesis (higher quality the better) in order to train a speech recognition system to a previously unseen level of accuracy.
4) Given a proper algorithm, sites with security vulnerabilities can be discovered just from what is crawlable and most likely should not be accessed. From that list, and given the total number of unique websites contained in the database, you can calculate the ratio of harmful to potentially non-harmful websites and provide a risk threshold of any given link on any given page.
5) Provide a search engine that uses regular expressions on different sets of the data (metadata, tags, text, text in a specific tag, etc.) to present a search engine with a previously unseen level of accuracy (accuracy of the results is dependent on the individual doing the searching, not the systems ability to guess that by std::list, I didn't mean "Sexually Transmitted Diseases STD List" (seriously, http://www.google.com/search?sourceid=chrome&ie=UTF-8... has that as the second result).
Edit: I failed at formatting
(5) is an interesting idea. I'm stuck on what else in the meta stream you would want to search, but certainly giving the flexibility to search the tags as well could open up some interesting experiences.
Search based on content type, content language, with/without keywords, author. Honestly, if Google just put out #5 and charged for it, it'd be worth $10 a month to me.
I'd like to see which search results were clicked on for a given search, and then associate those sites. And then do an amazon style: people who landed at this site also went to _____. As well as other relations based on user browsing, not based on site links.
I really like this idea, though probably the other sites would be the same shown in the search results. Usually when people are looking for something, they just orderly open the search results.
I like this a lot. Sort of like Stumble Upon and other social discovery, but different, and implicit, versus explicit (via a Stumble for example).
I would use it to fight crime/corruption. It isn't too hard to identify people from a few google searches. Examples:
Food places near X will give you a good indication where they live and their income Find what they are searching during normal work hours. Often this will give you where they work. Searches of themselves.
Then just use this information to hunt them down or expose them.
Food places near X will give you a good indication where they live and their income Find what they are searching during normal work hours. Often this will give you where they work. Searches of themselves.
Then just use this information to hunt them down or expose them.
[deleted]
Such a massive privacy violation. How would you feel if you searched for "age of consent laws" to lay the smackdown on some Reddit debate (http://xkcd.com/386/) and the Feds came knocking on your door?
How would you know who's a criminal?
From their searches of course!
It comes up in criminal cases all the time -- when you're googling "age of consent laws" or "how to dispose of a dead body" it's pretty easy to establish premeditation, though that doesn't help with 'pre-crime'.
The GP may have been focused on finding known fugitives on the run.
It comes up in criminal cases all the time -- when you're googling "age of consent laws" or "how to dispose of a dead body" it's pretty easy to establish premeditation, though that doesn't help with 'pre-crime'.
The GP may have been focused on finding known fugitives on the run.
Create new tools similar to how Google, Yahoo and MS already do when leveraging this asset. I know this is somewhat a BS answer, but really what other answer is there? This is like asking the question "What new features should Google, Yahoo or MS build on top of their search?"
My initial thought was that maybe you could create an information business along the lines of ComScore. That seemed a bit pedestrian.
Overnight, I began to wonder if you could build a tool much like Farecaster, where you could help ad buyers understand the movement of pricing for keywords, and make predictions about when they will move up and down.
Overnight, I began to wonder if you could build a tool much like Farecaster, where you could help ad buyers understand the movement of pricing for keywords, and make predictions about when they will move up and down.
Download all of the porn on the internet. I'm only half joking.
I would keep the meta data and reverse engineer the algo!
Good luck with that. :) Solving the user acquisition problem may prove somewhat challenging, no?
Sell it to someone, who'd know what to do with it?
You know that bit in Office Space where they're asking each other what they'd do if they had a million dollars and one of the guys replies that he'd invest half in mutual funds and take the other half to his friend who works in securities?
You're that guy now :-)
You're that guy now :-)
Yeah, you got me, ok. But somebody would say this eventually, I saved this somebody's ass, didn't I?
I wouldn't create a business. I'd write a program that could learn (text-based) language. Then I'd write it up and submit it to Computational Linguistics. Then I'd die in obscurity as someone took my idea and figured out how to monetize it.
Start the world's most underhanded (and successful) SEO firm.
Better machine translation.
This scenario is reminiscent of what happened a few years back when AOL released their whole corpus of search queries with associated user-ID hashes. Most of what was done with that data set amounted to amateur CSI work and general meanness. I don't recall any profound revelations or can't-miss business opportunities coming out of it. The value of raw data is overrated.
AOL released the list of searches created by users, purportedly anonymized. You didn't have access to the index of their crawler. Also, their subset was really small. I'm talking about a continuously updated stream.
I have started learning about complex event processing (CEP) and am wondering if you could do anything with that as a model tied to suggesting related links/sites.
I have started learning about complex event processing (CEP) and am wondering if you could do anything with that as a model tied to suggesting related links/sites.
One of my friends posed this question to me on Friday and my brain seized up. Creating another search engine made no sense, but the massive size of the data set and potential possibilities actually made my brain shut down.
What would HN folks do?