The Semantic Search Race Is On

Michael Vizard

Most search engines used on the Web today are little more than blunt instruments. They rely primarily on keywords and metadata tags to identify content that theoretically is related to a particular search query. As such, it doesn't take much for a website to "optimize" the keywords and metadata tags to target queries that the owner of that site wants to be ranked pretty highly. Of course, when everybody who has a website starts optimizing for the same keywords, it's not long before Web searches become an exercise that generates an increasing amount of useless results.


The folks at Google have acknowledged this fundamental search flaw by signaling that the company is working on incorporating more semantic search capabilities into its search engine. Known as "Knowledge Graph," the idea is to make the search engine smart enough to recognize what words on a page are related to each other. Once identified, the search engine should be able to return more useful results for any particular query, while also reducing its dependency on any particular keyword or metadata tag.


In 2010, Google acquired open source semantic search technology called Freebase, which the company is slowly incorporating into its core search engine platform. The concept of semantic search, however, has been around for a while and there's no doubt that other major search engine platforms are working on what many people view as "The Holy Grail" of search engine technology.


But what may be more interesting in the short term is that individual websites are beginning to make use of semantic search to compete more effectively within a narrow range of topics. For example, Monster.com last month began aggressively promoting its latest implementation of the 6Sense semantic search technology that it acquired in 2008 when it purchased Trovix.


According to Nikos Livadas, director of sales for North America for Monster.com software and cloud solutions, this capability not only helps prospective job candidates sort through postings, it makes it a whole lot easier for employers to sort through thousands of resumes to find the right job candidates for a particular position without having to rely on a simple keyword-based query.


Livadas says that semantic search actually heralds a new era of search-driven business intelligence that over time will make website and application software significantly more useful than they are today. The ability to provide those search-driven BI capabilities should prove to be a major point of competitive differentiation in the years ahead.


Whether it's because a handful of companies dominate the category or simply the difficulties associated with mastering technologies such as semantic search, the entire search engine category for the last several years has been fairly stagnant. However, it looks like that may finally be about to change for the better.



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