Hi All,
I'm wondering if anyone can link me to any literature on this matter and/or offer an opinion.
Search is problematic at the best of times. People frequently search 'poorly' using single terms. At TRIP the most frequent search terms are single disease areas (e.g. diabetes, hypertension) that yield large numbers of results. One thing I'm interested in exploring is can we infer the search intention from the background of the searcher. My thinking is based on a scenario such as 'diabetes'. If you're a UK psychiatrist you are likely to have different information needs than, say, an American diabetologist and different again from a Malian nurse. However, the same search terms are used and the same results returned. In the examples I've highlighted two variables - geography and speciality. But, there could be others e.g. 'rank' (e.g. a newly qualified GP will likely have different information needs to a GP nearing retirement).
Does anyone know of any literature that might explore these issues?
moving on, and using the above example we could see what paper most psychiatrists look at for the search 'diabetes' (it might normally appear in position 9 of the search results) and for future boost the placement for subsequent psychiatrists searching for diabetes. That';s the high level idea (so no expansion on things such as filter bubbles, clicking=like) etc.
I'd never intend to subvert the TRIP algorithm, but allow users to boost their results - if they want to. But does it sound reasonable?
BW
jon
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Jon Brassey
TRIP Database
http://www.tripdatabase.com/
TILT
http://tilt.tripdatabase.com/