I am expecting significant growth in the semantic search market over the next five years with most of it focused on enterprise search. The reasons are pretty straightforward:
- Semantic search is very hard and to scale it to the Web compounds the complexity.
- Because the semantic Web is so elusive and results have been spotty with not much traction, it will be some time before it can be easily monetized.
- Like many things that are highly complex, a good model will be to break the challenge of semantic search into smaller targeted business problems where focus is on a particular audience seeking content from a narrower domain.
I base this predication on my observation of the on-going struggle for organizations to get a strong framework in place to manage content effectively. By effectively I mean, establishing solid metadata, governance and publishing protocols that ensure that the best information knowledge workers produce is placed in range for indexing and retrieval. Sustained discipline and the people to exercise it just aren’t being employed in many enterprises to make this happen in a cohesive and comprehensive fashion. I have been discouraged by the number of well-intentioned projects I have seen flounder because organizations just can’t commit long-term or permanent human resources to the activity of content governance. Sometimes it is just on-again-off-again. What enterprises need are people with deep knowledge about the organization and how its content fits together in a logical framework for all types of knowledge workers. Instead, organizations tend to assign this job to external consultants or low-level staffers who are not well-grounded in the work of the particular enterprise. The results are predictably disappointing.
Enter semantic search technologies where there are multiple algorithmic tools available to index and retrieve content for complex and multi-faceted queries. Specialized semantic technologies are often well suited to shorter term projects for which domain specific vocabularies can be built more quickly with good results. Maintaining targeted vocabulary ontologies for a focused topic can be done with fewer human resources and a carefully bounded ontology can become an intelligent feed to a semantic search engine, helping it index with better precision and relevance.
This scenario is proposed with one caveat; enterprises must commit to having very smart people with enterprise expertise to build the ontology. Having a consultant coach the subject matter expert in method, process and maintenance guidelines for doing so is not a bad idea but the consultant has to prepare the enterprise for sustainability after exiting the scene.
The wager here is that enterprises can ramp up semantic search with a series of short, targeted projects, each of which establishes a goal of solving one business problem at a time and committing to efficient and accurate content retrieval as part of the solution. By learning what works well in each situation, intranet web retrieval will improve systematically and thoughtfully. The ramp to a better semantic Web will be paved with these interlocking pieces.
Keep an eye on these companies to provide technologies for point solutions in business critical applications: Basis Technology, Cognition Technology, Connotate, Expert Systems, Lexalytics, Linguamatics, Metatomix, Semantra, Sinequa and Temis.
Thanks Lynda! We agree domain expertise often comes into play and in particular your comment that “by learning what works well in each situation, intranet web retrieval will improve systematically and thoughtfully.”
I am just catching up on reading and discovered this article that I had set aside by David Weinberger and why the Semantic Web is such a distant vision. I should have cited it in the article as another reason that short term gains in enterprise semantic search have much greater potential. http://tinyurl.com/caxqnr Let’s just keep nibbling around the edges through progressive gains in the enterprise.