Last year my colleague Jonathan Young wrote a blog post Untangling the Semantic Web: Finding Threads of Gold, in which he noted that "Although the semantic web sounds like a panacea in theory, it does not have a great track record in practice."

At least one reader took this to mean we don't find the core problem interesting. Nothing could be further from the truth! A plurality of our customers and partners place great value on understanding and discovering entities and the relationships between them. Jonathan goes on to explain this later in his post - "...in designing [AIE] we picked a few of the golden threads from the semantic web and combined them with a number of techniques which have been shown to improve the search experience". Some of the relevant capabilities include:

• Dictionary and statistical named entity extraction in multiple languages

• Regular expression extraction of any pattern, including common natural language templates like "Sid Probstein is the CTO of Attivio"; you can combine named entity discovery with other search, e.g., find the term "Attivio" near a person entity, etc...

• Relationship modeling, e.g., friend-of-a-friend, using our query-side JOIN() operator.

What is Social Search? Is it simply having the ability to tag a result you found helpful and being able to share that with other users? Or is it more than that? Having the ability to tag results you like so it boosts the relevance for the next person enriches the search experience, but I would expect this capability to be available out-of-the-box for any platform that deals with information access. While being able to tag a useful result is, well, useful, there is a lot more to the story when you use the term social in combination with search.

When I think of social search, I think of the ability to pull content together from multiple social media platforms and combine it with internal content to provide my users with a full view of the information landscape.