Most of the main internet search engines leverage human intelligence to find relevant documents based on keywords. One way that page rank algorithms leverage human intelligence is by analyzing the hyperlinks that people use to point to other web pages.
When I search for something that was published ten years ago, there's a good chance my keyword search will work because over time other people have searched for and found the same document.
One of the things I've learned from my co-workers in Beijing is that personal, private information search is a very different problem to solve. The information is isolated from the internet, and therefore algorithms that leverage human intelligence for internet-based search are not applicable. Nobody is hyper-linking to personal information because it is hidden.
This means that if I am searching 10 years of personal documents, email, web pages, photos, music, tax records, newsletters, homework, etc., I may see search results that don't give me what I'm looking for.
My co-workers, realizing that human intelligence can be quite effective for internet-based search, wondered whether or not algorithms for private search could leverage the human intelligence found in one person (as opposed to thousands). This exercise led them down the path of associative memory.
Consider a person trying to find a specific picture from five years ago. Keyword search of their desktop is ineffective. But they remember what they were doing when they first saw the picture; they were emailing a specific relative on a specific holiday. If there was a way to feed this associate information into the search algorithm, then human intelligence indeed would help narrow down the search quite a bit.
This unique approach to the search of personal information has resulted in quite a flurry of research and university collaboration in China. The resulting prototype software to test this theory, iMecho, has been presented at a conference in Hong Kong. The idea was met with great enthusiasm. iMecho forms associative links while you are going about your daily personal business; these links can then be input into a search algorithm to more effectively find personal content.
I see a lot of promise for this research. One of the reasons the topic is so relevant in China is the general reluctance to post personal information onto common websites such as Facebook. If the Chinese population eventually moves towards public cloud paradigms for their personal information, the associative search patterns kept on local PCs could in theory be securely applied against information which is found inside of a public cloud.
Congrats to the Beijing team for coming up with such a cool idea. In fact, a subsequent paper describing their work was accepted into the SIGMOD conference in the USA last year (only the 8th time a Chinese paper has been accepted at SIGMOD since 1995).