How Google Tackles Synonyms in the Search for AI
Google says it has improved the way its search engine understands synonyms. Called semantic search, or even artificial intelligence for the especially geeky, parsing synonyms is something that search engine startups such as Hakia, Yebol and Microsoft's Powerset (now powering Bing) also work on. For example, if a user searches for information about how to develop photographs using coffee grinds as a developing agent, a search engine needs to understand that words such as photos and pictures could also be relevant.Google Jan. 19 said it has improved the way its search engine understands synonyms, a big step in the company's effort to make its search services think more like humans, or artificial intelligence, in the parlance of the computing industry. Parsing synonyms is something that search engine startups such as Hakia, Yebol and Microsoft's Powerset (now powering Bing) also work on, under the banner of semantic search. The idea is to fine-tune search engines to distinguish among words with similar meanings.
Google search quality engineers have racked up more than five years of research leading to the company's "synonyms system" by which it "analyzes synonyms' impact and quality," wrote Google Software Engineer Steven Baker in a blog post Jan. 19. "Our systems analyze petabytes of Web documents and historical search data" to understand "what words can mean in different contexts."
"Most people know the most prominent meaning: General Motors. For the search [gm cars], you can see that Google bolds the phrase "General Motors" in the search results. This is an indication that for that search we thought "General Motors" meant the same thing as "GM." ... GM can mean George Mason in [gm university], gamemaster in [gm screen star wars], Gangadhar Meher in [gm college], general manager in [nba gm] and even gunners mate in [navy gm]."How accurate is Google's treatment of synonyms? Baker said, "For every 50 queries where synonyms significantly improved the search results, [Google] had only one truly bad synonym." Meanwhile, users who stumble across poor synonyms should know a couple things. One, the AI behind synonyms isn't perfect, and two, Google will not manually fix bad synonyms because it prefers to make iterative improvements to its search algorithms. Baker invited users post questions at the Web search help center forum or to send them via Twitter with the hash tag #googlesyns. Users may also turn off a synonym for a specific term by adding a "+" before it or by putting the words in quotation marks. Matt Cutts, one of Google's search quality engineers, cheered Baker's post and called for Google to provide more transparency into its search quality efforts. He also threw down the gauntlet to challenge search rivals such as Bing, noting:
"The truth is that Google does a lot more sophisticated stuff than most people realize. I'd say that Google does more with "semantics" and both document and query understanding than almost any other search engine."