I attended a WebGuild event few months ago on the topic of Social Search and saw some interesting demos from sites like Mahalo (human power search engine) and Eurekster (search meets wiki). My instant reaction was mixed: how would the result-refining task ever work on a large scale? how to measure the quality of a search query? Is collaborative filtering a good or bad thing for the users?
I am not an SEO expert, so purely speaking from a user’s perspective, I would choose variety over accuracy since I believe “diversified definitions” is exactly what makes the Web so attractive compared to other media. That being said, I am pretty happy with the way search works today, and I think tagging as opposed to ranking, is where improvement is needed.
I goggled “better search algorithm”and this article ranks second on the first page. Here is a direct quote:
What if we had an “open source” search engine that everyone working in and around the area of search could plug into? The companies working in tagging, shared searching, audio and video search could offer their results/indexes to the open source search engine so that their meta data could be considered in preparing the best results?
With the above being said, this post was a result of what came into my mind after seeing the video demonstrating Google’s Digg-like search interface on TechCrunch this morning.
