[Search-l] blog bit: Radar’s Twine: A semantic Google killer?

[David Hart]

Radar's Twine: A semantic Google
killer?<http://feeds.feedburner.com/%7Er/Siliconbeat/%7E3/171898687/>
from
VentureBeat<http://www.google.com/reader/view/feed/http%3A%2F%2Fventurebeat.com%2F%3Ffeed%3Drss>by
Chris Morrison

[image: twine-logo.jpg]More than a year of secrecy spawned rumors about Radar
Networks <http://www.radarnetworks.com/>. The most popular: It's a "Google
killer." Tomorrow morning, Radar will surprise a few people by launching
Twine <http://www.twine.com/>, a tool for collecting and organizing
information that's very different from Google. But it's potentially just as
ambitious.

An example of how Twine <http://www.twine.com/> works: A user uploads a text
document to their Twine account. Twine then parses the document to find the
words with meaning — names, places, concepts and so forth. Those terms
become tags, which the person can use to access related information.

Twine's underlying technology gives the computer a measure of intelligence.
Using tags, a computer can distinguish between, say, a reference to the kind
of bird that flies and the kind that flips people off. Once it has, it can
give users a wealth of other information, drawn from their own accumulated
knowledge base, other users and the outside internet. Where Google crawls
the entire web and ultimately pollutes your search results with different
kinds of "birds," Radar picks from a smaller universe of sources and tries
to automatically discard the ones you don't want.

That could help a marketer collect all the information about a particular
product, or a group of analysts to aggregate information on a subject. The
"documents" gathered will include, among many others, text, PDFs, or even
videos on YouTube (Twine simply draws on pre-existing tags and description
of visual media to do its tagging work).

The information that helps Twine make decisions on its own about what
content to pull in for you comes both from a users' accumulated information
as well as their actions, which means that, as the user pulls more info into
their account on their own, Twine will begin to work cooperatively,
providing more content where it's needed and even assisting groups or teams
of people with collaborative research and knowledge-building.

Young companies with a limited ability to do similar selection tricks — for
instance, Jiglu, which we posted about a few days ago — are increasingly
common, and tend to obscure the companies that truly have a chance of
becoming market leaders. That's too bad, because there's no question that
intelligent computer handling of data — a first step toward artificial
intelligence — will be an important part of the internet in coming years.

Helping Radar is the breadth of its underlying technology and the strong
scientific and engineering team, now 30 strong, that has been working on the
platform for years.

Radar does, however, have competitors. The winning bet will boil down to
which company will be able to throw enough scientific brilliance at the
difficult problem of teaching computers to understand human information. The
winner will likely dominate, as Google does with search.

To explain the differences between these competing startups, it's easiest to
separate them by the particular types of technology they utilize.

Broadly speaking, those technologies fall into three categories. The first
is statistical analysis, in which Google reigns supreme. Terms are examined
for their frequency, placement and outside links to determine their apparent
relevancy, and then ranked. Google's algorithms have gotten better over the
years, and it has incrementally added on other technologies and services.

Natural language search is the second category. Teaching computers to
understand human language is a complex process which involves breaking
sentences down to their component parts — nouns, verbs, adjectives and so
forth — which can then take on symbolic meaning for computers. Powerset
(previous coverage), which is dribbling out its technology in stages, is a
prime example of this approach.

The third, semantic search, is much-hyped, but little understood. Simply
put, people attach markers to human-generated content, whether a paragraph
of text or a picture, to outright tell computers in a special machine
language what's meaningful. In these databases of these companies, for
example, I might be identified as "Chris Morrison," with the markers
"writer," "venturebeat," "male," "technology," "charming" and "goodlooking."
(All true, of course.) If applied to the entire internet, the result could
be thought of as a giant, interrelated Wikipedia. Metaweb, which recently
launched Freebase, is attempting to create just that.

For the most part, each company is betting on its own core technology to win
the race. Radar hopes its own special combination of all three will take the
day — much like another secretive startup, Franz Inc.

To be fair, there's also a fourth, less glamorous approach which relies
almost entirely on humans. ChaCha and a forthcoming startup from Wikipedia
founder Jimmy Wales are two examples.

First, though, the viability of any technology must be proven. To return to
Twine, it's the horse Radar is betting on, just as Powerset hopes to take
the approach of slowly beating out Google at searching the internet.

What matters is how well Twine can perform at helping humans organize the
avalanche of information that is modern life. So while there are other
features we could mention, from adding content through an innovative
bookmarklet to finding related content through a "social graph" of similar
users, it's more useful to give our reaction to Twine.

Having sat through a demo by founder Nova Spivack, we can say that we're
excited to try out Twine. The interface is simple, yet powerful. While the
use of tagging resembles tag-lists that have been around for years, their
application is clearly more useful. And Twine was obviously capable of
completing some complex tasks, like distinguishing the person's name J.P.
Morgan from the company with the same name.

The site is just as obviously still in development. A wealth of other
features could obviously be useful, from a more full array of choices for
communicating with other users (Spivack says instant messaging is coming) to
adding more possibilities for linking information.

However, the Twine team won't have to do the work alone. Sometime after the
current beta launch, which will be limited to a few thousand people, Twine
plans on opening up several APIs to allow outside developers to work with
the platform.

For now, the site is geared toward people who use the internet heavily —
primarily knowledge professionals, like the marketers and analysts mentioned
above. Students, prosumers (people with a strong interest in a particular
thing) and companies will also likely find uses for Twine.

For more discussion of Radar's idea of the future — including what could go
wrong — we'll post a Q&A with Nova Spivack on Saturday

[image: twine-greentech.jpg]

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