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306 Part Two Information Technology Infrastructure

Arguably, fewer than half. Google, Yahoo, Microsoft, and Amazon are all trying
to increase the odds of people finding meaningful answers to search engine
queries. But with over 400 billion Web pages indexed, the means available for
finding the information you really want are quite primitive, based on the words
used on the pages, and the relative popularity of the page among people who
use those same search terms. In other words, it’s hit or miss.
To a large extent, the future of the Web involves developing techniques
to make searching the 400 billion public Web pages more productive and
meaningful for ordinary people. Web 1.0 solved the problem of obtaining access
to information. Web 2.0 solved the problem of sharing that information with
others and building new Web experiences. Web 3.0 is the promise of a future
Web where all this digital information, all these contacts, can be woven together
into a single meaningful experience.
Sometimes this is referred to as the Semantic Web. “Semantic” refers to
meaning. Most of the Web’s content today is designed for humans to read and
for computers to display, not for computer programs to analyze and manipu-
late. Semantic Search, described above, is a subset of a larger effort to make
the Web more intelligent, more human like (W3C, 2012). Search engines can
discover when a particular term or keyword appears in a Web document, but
they do not really understand its meaning or how it relates to other informa-
tion on the Web. You can check this out on Google by entering two searches.
First, enter “Paris Hilton”. Next, enter “Hilton in Paris”. Because Google does
not understand ordinary English, it has no idea that you are interested in the
Hilton Hotel in Paris in the second search. Because it cannot understand the
meaning of pages it has indexed, Google’s search engine returns the most pop-
ular pages for those queries where “Hilton” and “Paris” appear on the pages.
First described in a 2001 Scientific American article, the Semantic Web is a
collaborative effort led by the World Wide Web Consortium to add a layer of
meaning atop the existing Web to reduce the amount of human involvement
in searching for and processing Web information (Berners-Lee et al., 2001).
For instance, in 2011 the New York Times lanched a semantic application
called Longitude which provides a graphical interface to access the Times
content. For instance, you can ask for stories about Germany in the last 24
hours, or a city in the United States, to retrieve all recent stories in the Times.
(Donaldson, 2012).
Views on the future of the Web vary, but they generally focus on ways to make
the Web more “intelligent,” with machine-facilitated understanding of informa-
tion promoting a more intuitive and effective user experience. For instance,
let’s say you want to set up a party with your tennis buddies at a local restau-
rant Friday night after work. One problem is that you are already scheduled
to go to a movie with another friend. In a Semantic Web 3.0 environment, you
would be able to coordinate this change in plans with the schedules of your
tennis buddies and the schedule of your movie friend, and make a reservation
at the restaurant all with a single set of commands issued as text or voice to
your handheld smartphone. Right now, this capability is beyond our grasp.
Work proceeds slowly on making the Web a more intelligent experience, in
large part because it is difficult to make machines, including software programs,
that are truly intelligent like humans. But there are other views of the future Web.
Some see a 3-D Web where you can walk through pages in a 3-D environment.
Others point to the idea of a pervasive Web that controls everything from the
lights in your living room to your car’s rear view mirror, not to mention manag-
ing your calendar and appointments. This is referred to as the “Web of things.”

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