New gen next search engines for personalised results

Online search just got easier!
Researchers have developed a new way for search engines to provide users with more accurate, personalised search results.
The challenge in the past has been how to scale this approach up so that it doesn't consume massive computer resources.
Now, researchers from the North Carolina State University have devised a technique for implementing personalised searches that is more than 100 times efficient than previous approaches.
The issue was how search engines handle complex or confusing queries. For example, if a user is searching for faculty members who do research on financial informatics, that user wants a list of relevant webpages from faculty, not the pages of graduate students mentioning faculty or news stories that use those terms.

"Similarly, when searches are ambiguous with multiple possible interpretations, traditional search engines use impersonal techniques. For example, if a user searches for the term 'jaguar speed' the user could be looking for information on the Jaguar supercomputer, the jungle cat or the car," said Dr Kemafor Anyanwu, senior author of the research.

"At any given time, the same person may want information on any of those things, so profiling the user isn't necessarily very helpful," said Anyanwu.
Anyanwu's team has come up with a way to address the personalised search problem by looking at a user's "ambient query context," meaning they look at a user's most recent searches to help interpret the current search.

Specifically, they look beyond the words used in a search to associated concepts to determine the context of a search.
So, if a user's previous search contained the word "conservation" it would be associated with concepts likes "animals" or "wildlife" and even "zoos."
Then, a subsequent search for "jaguar speed" would push results about the jungle cat higher up in the results - and not the automobile or supercomputer.
And the more recently a concept has been associated with a search, the more weight it is given when ranking results of a new search.
Search engines have also tried to identify patterns in user clicking behavior on search results to identify the most probable user intent for a search.

However, such techniques are impersonal and are applied on a global basis.
So, if the most frequent click pattern for a set of keywords is in a particular context, then that context becomes the context associated with queries for most or all users - even if your recent search history indicates that your query context is about jungle cats.