Automated Assistance (i.e. system help or searching help) for Web Searching

One of the most potentially useful, yet difficult to achieve, technologies has been a sophisticated and useful system assistance during the searching process.

Certainly, there has been some system assistance that has been really useful. Probably the most successful and worthwhile has been the spelling suggestions for query terms.

Several Web search engines from Excite onward have attempted various forms of query reformulation or query suggestions. There have been some other attempts, such as relevance feedback. However, not too much advantage.

Much of the system assistance research has focused on personalization, usually employing some type of implicit feedback (i.e., drawing inferences from user – system interactions). Implicit feedback has some advantages over explicit feedback approaches (such as document ratings and profiles), namely the participation rates are much better.

However, the results from this line of research have been less than stellar. Most research results show little to no improvement in searching performance. Personalizing at the individual level may be just too difficult or a dead end.

A more worthwhile avenue of investigation may be to (1) identify what the user is seeking in terms of content and (2) personalized at this aggregate level. This approach seems to have promise.

Here are three papers that I have done on using implicit feedback for automated assistance / system help:

http://ist.psu.edu/faculty_pages/jjansen/academic/pubs/jansen_cacm_2006.pdf
http://ist.psu.edu/faculty_pages/jjansen/academic/pubs/jansen_assistance_jasist2005.pdf
http://ist.psu.edu/faculty_pages/jjansen/academic/pubs/jansen_assistance_IPM05.pdf