June 28, 2005
In my research on a new collaborative project meme.garden (with d. howe) I happened to re-explore some ‘commonsense’ databases including the commonsense project at MIT, “open mind.” After various approaches to making effective search engines, this one–with its reliance on real people’s knowledge aggregated over time–seems promising.
Yet such a system is rife with problems, as one can imagine. It is criticised by some net researchers and bloggers for containing too many ‘garbage’ entries to be efffective, and just plain factual errors by those who might even mean well.
Liu, Lieberman, and Selker at MIT are engaged in the mission of making better searches. In their 2002 article on a proposed search engine ‘goose’, they discuss the act of problem solving in searches; among other threads, they research the ways that people move from goals to actual key words in their searches, tracking inference chains. The authors note that most searches either use
1) thesaurus style tools to expand topics
2) ask for relevance feedback from users
3) use question templates (such as those used in Ask Jeeves).
I’ll be posting other related search engine material while researching…