For Once I Oneder

I’ve been working on and off on a writeup concerning the use of Beagle to build an intelligent ‘rank’ for desktop entities. Or, in short, a Ranking system (not unlike Page Rank or the like) to organize desktop search results by far more than just keyword/date. I know the writing sucks, and its not 100% complete yet. In addition, I don’t have much in terms of code to share (yet).

To summarize (for those lazybones out there) I’m thinking of utilizing fairly universal and constant relationships (Creator, Creation Date, Modification Date(s), Parent/Source, and maybe others) to recurse deep into desktop relationships. By adding relevancy to the root hit for every child it has (logarithmically decreased by recurse iteration) we can have far more accurate desktop search results when querying a simple keyword/phrase. In addition, the children of a hit could often be considered hits themselves, if found in enough ‘root’ hits.

Its a loose and patchy idea, and miles from a realistic implementation, however, thanks to the awesomeness of Lucene, comparing 2 in-index documents for textual relevancy (based on Term Frequency) is not impossible. (I have not considered the performance elements of these comparisons yet, they may be too slow to be realistic without serious optimization)

Anyways, I’m working on it in Google Docs, so you can check out the full document here. I’ll post once I’ve finished my research/planning etc.

Please, share your thoughts! This is in the ‘major brainfart’ stage, so its open to whatever from anyone, I want to hear ideas!

Technorati Tags: beagle, desktop search, lucene, search rank, gnome, mono

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