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Google improves search with semantic technology

Search engine now recognizes associated phrases

Google has improved its search engine with the use of semantic technology, which it claims will enable the search engine to identify associations and concepts related to a query, improving the list of related search terms.

For example, Google's search engine, upon encountering a query like 'principles of physics', now understands that 'angular momentum', 'special relativity', 'big bang' and 'quantum mechanics' are related terms, the company said in a blog.

Ori Allon, technical lead of Google's Search Quality team, said the search improvement involves a dollop of semantic search technology mixed in with a big helping of lightning-fast, on-the-fly data mining.

"This is a new approach to query refinement because we're finding concepts and entities related to queries while you do a search, so everything is happening in real time and not [pre-assembled]," he said. "Because we're doing it in real time, we're able to target many more queries."

The use of semantic search isn't more broad at this point because full conceptual analysis of documents would slow down the process of generating query refinements on the fly, Allon said. "If we want to get it all done in a matter of milliseconds, there's a lot of innovations we still have to do. A full semantic search would be very hard to do in this limited amount of time," Allon said.

This is a big stumbling block that semantic search engines often run into: scaling their technology to the speed and volume of a massively used service like Google's.

"We're working really hard at search quality to have a better understanding of the context of the query, of what is the query. The query isn't the sum of all the terms. The query has a meaning behind it. For simple queries like 'Britney Spears' and 'Barack Obama' it's pretty easy for us to rank the pages. But when the query is 'What medication should I take after my eye surgery?', that's much harder. We need to understand the meaning," said Allon.

"The main Google infrastructure now is able to have a better sense of what is the context of the query and what are its related concepts, and how they relate to each other," he said. "So this is the first of what we hope will be many other applications that we're working hard to incorporate into search quality."

There is an entire field of Google competitors that are busy developing and perfecting semantic search engines, betting that they will be able to deliver on the promise of this technology: to let users type in queries in natural language and have the search engine understand their meaning and intent.

Microsoft last year acquired Powerset, one of these companies, in order to improve its web search engine with semantic search technology.

Google also rolled out another enhancement to its search engine: longer 'snippets', which are the text excerpts Google extracts from websites to show in search results where the query keywords appear.

It remains to be seen if website publishers will cry foul over longer snippets. In the past, publishers have sometimes complained that search engine abstracts that are too long give away too much of their sites' content. This in turn, they say, could cause potential visitors to not click over to the page, particularly if the abstract, or snippet, gives them the information they're looking for.

This is an area where search engines have to strike a delicate balance between fulfilling their mission - giving their users the most precise information possible related to their query - and not violating the copyrights of website publishers.


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