On Tue, 2006-06-06 at 22:23 +0000, michael turner wrote: > Working on a project that requires a Search query similiar to what is > seen on"amazon.com" in that after searching for and displaying an item, > the system shows: > > "Users that have searched for "AAAAA" AND "BBBBB" have also searched > for "CCCC". > > Where "BBBBB" and "CCCC" are other related entities. > > > 1. Has anyone used or heard of this algorithm?
A quick and dirty reply: Actually, Amazon does not track the queries, they track what customers buy. The "algorithm" you are looking for is collaborative filtering. You would probably want to build a classification scheme much more detailed than the formula 1-a facets in order to get good results. To find such clusters based on searches is tricky as you only want to take the results that was relevant in to account. If you only want to find some statistics of how people refine or change their queries to find what they are looking for, then you need to know the original query and the end query, and be really sure that the subject of the search did not change. Overlap all sessions you saved and use some statistical analysis library (perhaps Weka can help you?) to get the results. It might also be possible to implement using hidden markov models. You really have to tell us more about the application you add Lucene to in order to get a good reply on how to implement a suggestion scheme. --------------------------------------------------------------------- To unsubscribe, e-mail: [EMAIL PROTECTED] For additional commands, e-mail: [EMAIL PROTECTED]
