How’s that for an alliteration?
Back in 2007, Dave Copps introduced us to PureDiscovery at the very first SourceCon conference, and in doing so he opened the door to semantic search for many of us in the sourcing world. Semantic search is not a new concept, but it’s one that alludes many of us because it’s just one of those things that has a bit of a fuzzy definition.
Semantics, by its purest definition, is the study of the meaning of something, usually a language. This is not to be confused with syntax, which is the grammatical arrangement of words in sentences. Semantics is more about the words chosen to share a message, where syntax is more about how those words are arranged within the message. The two are interconnected, but they will take you in different directions when you search.
The term semantic web refers to how our computers and internet technologies take a look at the information out there on the Web and make sense of the meaning of it all. This specifically includes social networks because a lot of what’s contained in social networks are thought streams of individual people. The original idea of a semantic web is credited to World Wide Web Consortium (W3C) director Tim Berners-Lee, when he shared the following thought back in 1999 in his book “Weaving The Web“:
“I have a dream for the Web [in which computers] become capable of analyzing all the data on the Web – the content, links, and transactions between people and computers. A ‘Semantic Web’, which should make this possible, has yet to emerge, but when it does, the day-to-day mechanisms of trade, bureaucracy and our daily lives will be handled by machines talking to machines. The ‘intelligent agents’ people have touted for ages will finally materialize.”
The purpose of semantic search technology is to understand the intent of the searcher. What semantic search engines do is look at words surrounding words and attempt to “disambiguate” them. Lots of words have multiple meanings, and semantic search technology takes a look at the context in which the words appear and attempts to clarify what it believes the intent of the searcher is. The hope of those who create semantic technologies is that they will learn search patterns over time and be able to better predict what the human searcher is trying to find. (see Google’s most recent Instant Search product release)
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The technology behind semantic search engines is quite complicated. But we thought it might be nice to examine some of these search engines a little more closely to see how they can be useful to us in our daily sourcing functions. So in the coming weeks, we will be reviewing several semantic search tools. This will include (but is not limited to):
If you’d be interested in conducting a review of a semantic search tool that can be posted as part of this series, please let us know as well. We’d love to include as many tools as possible to give sourcers some good information on semantic technologies and how they will be helpful to us as we search for leads and candidates.