Taking advantage of Natural Language Processing (NLP), a competitor to Flipboard indicates what big data projects crawling the web for content and sentiment have to look forward to.
Taking on Flipboard
Depressingly, for those of us who have left the light of youth behind and are still trying to make our mark on the world, Clipped was designed by a 15-year-old entrepreneur named Tanay Tandon. The Next Web describes Clipped as an "abridged version of Flipboard," which distills news down to its main bullet points, rather than delivering entire articles on a user's preferred interests.
The Clipped Logo
The project came about through the Teens in Tech Incubator, "an eight week hands-on program for entrepreneurs between the ages of 13-19 who are serious about building products and learning about entrepreneurship."
Natural Language Processing isn't solely the domain of big data work, but its use within big data sets makes it a great area of development for companies looking to wrangle meaning and use out of enormous data collections. It is certainly an area of expanding interest within the field, tied to extracting useful information from collected text datasets and performing meaningful and complex sentiment analysis.
The big data potential
At the moment, Clipped pulls content from 30 news sources, delivering truncated stories on specific topics. Those sources are news outlets (creators of data), and the output is a similar, streamlined flow of data.
Let's take a moment to imagine this spread to more sources -- or better yet, crawling the net freely. Tandon's incredibly clever NLP approach takes the leg work out of searching for mentions or discussions of topics. Applied more widely, this could pull information from international news sources, examining the most important, globally-seen points of texts. It could be let loose on social networks, to gauge opinion on retail products or educational syllabuses.
The big data reality
Given that most big data projects seem to be focused on mining internal data for insight on ways to cut cost and make businesses more efficient, it will only be the truly early adopters who take advantage of the technology Tandon has highlighted here. The beauty of NLP is its ability to slot into different tasks. A well-written, news-gathering algorithm could easily be applied to stock information or medical results.
How can you see your organization leveraging NLP in its big data ambitions?
Keith.Grinsted,
User Rank: Petabyte Pathfinder 3/31/2013 | 3:05:07 PM
Re: Then, if only.... @Saul yes, but just think if we could solve that problemnthen just how much quicker we would have even greater minds on board to solve all the other problems.
I think we are closer than we perhaps realise!
Saul Sherry,
User Rank: Blogger 3/4/2013 | 12:23:18 PM
Re: Then, if only.... It might be blue sky for the moment Keith... but the core principles could be put in place earlier - but i think we are much closer to buidling the perfect big data analytics stack than figuring out how dreams really work.
Keith.Grinsted,
User Rank: Petabyte Pathfinder 2/28/2013 | 1:06:18 PM
Then, if only.... ..we could have that fed into our minds while we sleep we'd be educated overnight with everything that has happened in the world in the previous 24 hours that has a bearing on our own lives and interests!!
Or has it simply been a long week and I'm doing some blue sky thinking?
Saul Sherry,
User Rank: Blogger 2/26/2013 | 6:08:55 AM
Re: entrepreneurs between the ages of 13-19 @alphaedge as far as I can see nlp in this case is taking a lot of the leg work out of the process (content arrives pre-filtered if you will). The use of this on sentiment analysis is obvious, reducing the load to the workable, important points so you don't have to... as to its speed, it remains to be seen.
AlphaEdge,
User Rank: Exabyte Executive 2/25/2013 | 9:07:00 AM
Re: entrepreneurs between the ages of 13-19 NLP devlopment helps quite a bit on the sentiment analysis. Big data technologies certainly would help another leap ahead on the NLP. Just wondering what level of granuality of the NLP can get to? for example, it can help understand the sentiment in general, but it may not be the best tool yet at the moment for real time streaming data analysis.
netcrawl,
User Rank: Exabyte Executive 2/25/2013 | 7:39:05 AM
Re: entrepreneurs between the ages of 13-19 @Saul interesting article, its really great to see teens making a huge presence in technology field, I remember the americans during the cold war, when the russian launched the Sputnik, the US President made a huge challenge to counter the "Russian attack" by "launching its own version of Sputnik"-an american satellite, the teens build rockets in their own garage.
To save this item to your list of favorite Big Data Republic content so you can find it later in your Profile page, click the "Save It" button next to the item.
If you found this interesting or useful, please use the links to the services below to share it with other readers. You will need a free account with each service to share an item via that service.
Tweet This
