Sophia Search Lands Venture Funding
July 9, 2010
Wisdom is a good name for a search and content processing system. If you live in rural Kentucky, the Greek becomes “Sophia”, which denotes wisdom. (Gentle reader, “wisdom” is not highly prized in Harrod’s Creek.)
The news that Sophia Search (founded in 2007) landed $1.2 million in seed money reached me via Marketwire. The investors include Volcano, based in Belfast, and Javelin Ventures in London. The story’s title was effective in arresting my attention: “Sophia Search Secures Largest Angel Investment in Northern Ireland to Address Global Demand for Next-Generation Enterprise Search and Discovery.” The news item said:
Sophia’s technology is purpose built on the company’s unique, patented, Contextual Discovery Engine (CDE) based on the linguistical model of Semiotics, the science behind how humans understand the meaning of information in context. The CDE platform automatically detects relationships and themes in unstructured content to enable organizations to seamlessly search, extract, deduplicate and eliminate redundancy of content to minimize risk and reduce the cost of retrieving, storing and managing enterprise information.
The news story revealed that Sophia is built on a patented, next-generation search engine platform. The system can “automatically discover relationships and themes in unstructured content.”
The company, according to my notes, is a spin out from University of Ulster and Saint Petersburg State University. Sophia Search was one of the companies recognzed by the PricewaterhouseCooper entrepreneur competition. (Keep in mind that I do work for the outfit that help PricewaterhouseCoopers conduct these entrepreneur competitions.)
A quick trip to our Overflight system yielded some useful nuggets about this company. The Sophia Search white paper, dated January 2009, pointed out that the method is “fundamentally different to [sic] any other search tool.” The white paper continued:
These tools are based on ideas & principles drawn from disciplines such as Signal Processing or Mathematics. These ideas are ‘borrowed’ from these disciplines and applied to text retrieval to provide search. In Sophia we believe that in order to retrieve useful information for users we must first understand its meaning and as such we build Sophia upon the recognised linguistical model of Semiotics.
The system “understands” the context in which a word or phrase is used. The white paper said: “In order to understand the meaning of a word it must be taken within the context of other words around it.” We agree. Key word indexing is one reason why most search systems drive users to distraction.
The white paper introduces the idea of “intertextuality”. Here’s what the Sophia white paper says:
All texts are rehashes of previously existing ones and in order to understand them properly they must be read within the context of all information available that is related to them.
Many search engines remain ignorant of what has been previously processed. Google’s programmable search engine includes a context server which addresses this problem in the context of Ramanathan Guha’s method. But Google does not as far as I know offer its context server technology to third parties. Sophia’s engineers are heading down an interesting path in my opinion.
The system processes content, picks out key themes, and then clusters the pointers into “themes”. The idea is that a search rturns content which is “topically similar”. According to the write up in the University of Ulster’s U2B newsletter (Winter 2007), Dr. David Patterson, one of the founders of the company, revealed:
Sophia just doesn’t ind relevant information for customers, it also empowers them with an understanding of the meaning of the information returned. Using conventional search is akin to using a torch in a dark room (the torch represents the search engine and the room, an organisation’s information). Only the parts of the room that have the beam of light focussed on them can be seen at any one time, with limited understanding of the information in view. Using SOPHIA is like licking the switch for a bright ceiling light. The whole room can be seen and all information understood at once.
If you are into technical papers, you can get a feel for the system’s method in “Sophia: An Interactive Cluster-Based Retrieval System for the OHSUMED Collection,” published in 2005.
With some search systems fading, new entrants often find eager audiences. Will Sophia become a break out solution? We wish the Sophia team the best.
Stephen E Arnold, July 9, 2010
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