The research was the first published work of its kind done using
actual searching data, with the aim of real-time classification.
Researchers analyzed more than 1.5 million queries from hundreds of
thousands of search engines users. Findings showed that about 80
percent of queries are informational and about 10 percent each are for
navigational and transactional purposes.Jansen and his colleagues arrived at those results by selecting
random samples of records and analyzing query length, the order of the
query in the session and the search results. These fields helped the
team develop an algorithm that classified the searches with a
74-percent accuracy rate.“Other results have classified comparatively much smaller sets of
queries, usually manually,” Jansen said. “This research aimed to
classify queries automatically.“Our findings have broad implications for search engines and
e-commerce if they can classify the user intent of queries in real
time. This is why we wanted a computational undemanding algorithm,”
Jansen continued. “It proves the 80/20 rule that 80 percent of the
cases can be achieved with these clear-cut methods.”
Source: Science Daily
Via Unplain
Sahar - Interesting data - Thanks for the INFO.