Written by Ebrahim Ezzy and edited by Richard
MacManus. Ebrahim is lead developer and co-founder of Qelix
Technologies, the company behind a search 2.0 contender called Qube. This 2-part series of posts is adapted from
Ebrahim’s research material in developing Qube. [update Part 2 is here]
Let’s start be defining what we mean by “search 2.0” vs traditional search.
Traditional Search (TSE):
Traditional search engines are based on information retrieval technologies. They implement operations such as boolean queries, proximity searches, text relevance and
Examples: Google, Yahoo, MSN, Ask
Search 2.0 (S-2.0):
What I’m calling Search 2.0 are actually third generation search technologies. To
explain the generations:
- First-generation search ranked sites based on page content – examples are early
yahoo.com and Alta Vista.
- Second-generation relies on link analysis for ranking – so they take the structure of
the Web into account. Examples are Google and Overture.
- Third-generation search technologies are designed to combine the scalability of
existing internet search engines with new and improved relevancy models; they bring into
the equation user preferences, collaboration, collective intelligence, a rich user
experience, and many other specialized capabilities that make information more productive.
Examples: Swicki, Rollyo, Clusty, Wink, Lexxe
The Search 2.0 Companies (Pt 1)
Search is a multi-billion dollar market and a lot of startups want to be ‘the next
Google’ So lets take a look at what current hot technologies are shaping the future of
Swicki is a community-driven search engine that allows users
to create deep, focused searches on a specific niche. Search results from a Swicki are
more focused than a TSE and can learn and adapt automatically, based on the search
behavior of the community.
Key Feature: Pattern recognition and Adaptive filtering
How it is useful compared to TSE?: Sometimes, looking for specific information
in huge web indexes is so mystifying that users feel lost. Services like Swicki promise
to accelerate the evolution of Search, by providing hyper-contextual
(to use Mike Arrington’s term) search results.
Both Rollyo and Swicki pursue a similar goal: community
powered, theme-based search. Rollyo allows users to create and publish their own personal
search engines, based on websites they decide to include in their ‘SearchRoll’.
SearchRoll doesn’t replace a TSE, it’s just a great way to search your favorite things in
your favorite places.
Key Feature: Community-driven Search
How is it useful compared to TSE?: It narrows your search down to only a few
trusted sources. A welcome retreat from the current in-your-face information chaos of the
As the name suggests, Clusty is a clustering engine that groups similar items
together – organizing search results into folders. It goes beyond simple search and
combines the power of clustering with meta-search (i.e. a search of other searches), to
provide a productive and flexible search experience. As well as producing organic web
results, Clusty also enables searching of shopping information, yellow pages data, news,
blog posts and images.
Key Feature: Result Clustering
How it is useful compared to TSE?: The competition has shifted from crawling
the web and returning search results, to adding value to the information
that has been retrieved. Clusty has a few advantages over Google:
1) You don’t have to come up with your own categories or subjects in order to narrow,
or refine, the search.
2) You don’t have to rely on Google’s perceived emphasis on links.
3) You don’t have to guess the keyword, to get to that perfect page you need. Navigate
the clusters and sub-clusters, just as you would use eBay, to find that one specific
treasure you’ve been hunting for.
Using the power of social networking, Wink enables users to tag their favorite results, block
irrelevant spam and display the best sites – as hand-picked by other users.
Key Feature: Collaborative Search
How is it useful compared to TSE?: Humans can recognize spam better than any
automated filter. Social Search battles search manipulation (i.e. Black Hat
SEO) by allowing users to block spam directly. However, one issue is that this system
can be easily gamed. But if improved, Wink can deliver a leap in value to Web
does what TSE’s already do, but more efficiently. Lexxe is designed to extract short
answers on-the-fly, instead of finding the page on which the answer might be located. It
emphasizes the processing of language rather than symbols – using the level of words and
the meanings associated with them.
Key Feature: Linguistic Search
How is it useful compared to TSE?: Although they claim to be “50% more accurate and
relevant than any other search engine, including google”, I’m not convinced. However,
they do have mechanisms in place to determine fairly accurate answers for short questions,
compared to Google. For example: Who was Louis-Nicholas Vauquelin? Compare
Google‘s answer to
That wraps up Part 1 of our look into Search 2.0. In the next installment we’ll be
looking at other notable contenders like Jookster, Gravee, PreFound and Ebrahim’s own
company Qube. We’ll also address questions such as:
How is traditional search evolving to Search 2.0? Can Search 2.0 replace Traditional
Update:Part 2 of this series is available now, with more profiles plus an analysis of how traditional search is evolving towards social search.