By - Rachel Metz
Category - Website Design And Development
Posted By - http://tinyurl.com/WebDesign05
Website Design And Development |
Some web searches are easy to think of and describe, but complicated to conduct.
If, for instance, you want to find “a nonstop flight from Las Vegas
to San Diego next week on JetBlue,” you have to fill out a bevy of
fields on a travel site.
SkyPhrase, a startup created by Nick Cassimatis,
an associate professor at Rensselaer Polytechnic Institute, will soon
offer software that lets companies turn natural language questions like
the one above into a format that their databases can handle.
Facebook’s new search tool,
Graph Search, highlights both the progress that’s being made in natural
language processing and the difficulties that remain. Unlike the old
search bar, Graph Search lets users enter queries as they might speak
them. And yet, this is still limited to a fairly small range of query
types.
While natural language processing typically involves teaching
software vocabulary and grammatical rules or using statistical analysis,
SkyPhrase’s technology uses a combination of algorithms and data
structures.
The company plans to release a website in February, as well as an
extension for the Chrome web browser, that would allow users of Google
Analytics to filter information using natural language queries.
Cassimatis says this could make it easier to find patterns or data
points that are otherwise time-consuming for even a seasoned user to
unearth. Eventually, the company hopes to offer SkyPhrase as a
programming interface for other websites.
Natural language search could make it easier for people with little
or no training to ask complicated questions that typically require
searching through large stores of data. Besides Facebook’s efforts,
Wolfram Alpha can answer natural language queries, and Apple’s virtual
assistant Siri also encourages users to speak questions aloud in
complete sentences (some of its answers come from Wolfram Alpha).
Percy Liang, an assistant professor in Stanford’s computer science
department who studies natural language processing and machine learning,
thinks SkyPhrase’s idea is a good one, but cautions that there is a lot
of work to be done to make natural language processing work. He says
challenges include determining what a word or phrase means based on its
context—such as knowing that Obama is not just the U.S. president’s
name, but also a city in Japan—and the ability to pick up on
sentiment—such as a Yelp restaurant review that says, sarcastically, “I
had to wait an hour for this!”
Users also need to know what they can do with the system. If there’s a
big gap between a user’s expectations and the system’s abilities, the
user will get disappointed, Liang says. Facebook’s Graph Search, for
example, tries to solve this problem by auto-completing queries so users
know what kinds of things it can search for. Likewise, Siri tries to
answer only a limited range of queries.
SkyPhrase is still clearly in its infancy. I tried a version that can
conduct complex natural language searches of Twitter, Gmail, Orbitz and
Amazon’s MP3 store. It couldn’t understand a number of my queries—not
infrequently because I was trying to get it to do things it hasn’t yet
been trained to do—but it did a decent job of searching through Gmail,
and understanding some complex queries about e-mails I needed to find as
I organized an upcoming trip.
SkyPhrase understands only searches for complete words (a search for
simply “banana” won’t bring up an email mentioning the game Bananagrams)
and doesn’t infer meaning from words (it won’t pull up messages or
tweets with words related to the words you’re searching for). But it can
understand conjunctions—I could search for, say, “emails from Bob
Loblaw in December and January about recipes with a PDF,” or “emails
from Bob Loblaw or Tobias Funke about cookies in December.”