[SKRIVA] Datorn som lär sig språk

From: Ahrvid Engholm <ahrvid@xxxxxxxxxxx>
To: <skriva@xxxxxxxxxxxxx>
Date: Thu, 7 Oct 2010 10:25:23 +0200
Datorn NELL (The Never-Ending Language Learning system) har försetts med en del 
grundkunskap, och står nu på i en källarskrubb 24 timmar om dygnet och läser av 
World Wide Web för att lära sig språk, ungefär som människor:
 
http://www.nytimes.com/2010/10/05/science/05compute.html?_r=1&ref=science
 
"Few challenges in computing loom larger than unraveling semantics, 
understanding the meaning of language. One reason is that the meaning of words 
and phrases hinges not only on their context, but also on background knowledge 
that humans learn over years, day after day. 
Since the start of the year, a team of researchers at Carnegie Mellon 
University — supported by grants from the Defense Advanced Research Projects 
Agency and Google, and tapping into a research supercomputing cluster provided 
by Yahoo — has been fine-tuning a computer system that is trying to master 
semantics by learning more like a human. Its beating hardware heart is a sleek, 
silver-gray computer — calculating 24 hours a day, seven days a week — that 
resides in a basement computer center at the university, in Pittsburgh. The 
computer was primed by the researchers with some basic knowledge in various 
categories and set loose on the Web with a mission to teach itself. ...
The Never-Ending Language Learning system, or NELL, has made an impressive 
showing so far. NELL scans hundreds of millions of Web pages for text patterns 
that it uses to learn facts, 390,000 to date, with an estimated accuracy of 87 
percent. These facts are grouped into semantic categories — cities, companies, 
sports teams, actors, universities, plants and 274 others. The category facts 
are things like “San Francisco is a city” and “sunflower is a plant.” 
NELL also learns facts that are relations between members of two categories. 
For example, Peyton Manning is a football player (category). The Indianapolis 
Colts is a football team (category). By scanning text patterns, NELL can infer 
with a high probability that Peyton Manning plays for the Indianapolis Colts — 
even if it has never read that Mr. Manning plays for the Colts. “Plays for” is 
a relation, and there are 280 kinds of relations. The number of categories and 
relations has more than doubled since earlier this year, and will steadily 
expand. 
The learned facts are continuously added to NELL’s growing database, which the 
researchers call a “knowledge base.” A larger pool of facts, Dr. Mitchell says, 
will help refine NELL’s learning algorithms so that it finds facts on the Web 
more accurately and more efficiently over time."
 
--Ahrvid

--
ahrvid@xxxxxxxxxxx / Gå med i SKRIVA - för författande, sf, fantasy, kultur 
(skriva-request@xxxxxxxxxxxxx, subj: subscribe) YXSKAFTBUD, GE VÅR WCZONMÖ 
IQ-HJÄLP! (DN NoN 00.02.07)
Om Ahrvids novellsamling Mord på månen: http://www.zenzat.se/zzfaktasi.html C 
Fuglesang: "stor förnöjelse...jättebra historier i mycket sannolik 
framtidsmiljö"!                                          -----
SKRIVA - sf, fantasy och skräck  *  Äldsta svenska skrivarlistan
grundad 1997 * Info http://www.skriva.bravewriting.com eller skriva- 
request@xxxxxxxxxxxxx för listkommandon (ex subject: subscribe).
[SKRIVA] Datorn som lär sig språk

Other related posts:
