Gene Smith discusses a product idea from the recent past (Shreveport):
Shreveport is basically a search engine with some social software concepts layered on top. Here are some of its core concepts:
* Search terms are tags on an URL. Shreveport associates tags with URLs based on clickthroughs.
* Search history is shared. Search terms and selected results are shared in the same way del.icio.us shares tags and URLs. (Obviously, we’d thought about an opt-out feature for some searches…. you know, “athletes foot remedies” and the like.)
* Search terms and results selection help improve search results. Part of our largely hypothetical algorithmic mojo engine was a way to use improve results by tracking which links were selected for each query. (I wonder if anyone’s doing this now?)
* Exploration and recommendations. Users can explore tags, URLs, users and their visited results. For each search they see weighted recommendations (“People who searched for ‘celiac disease’ also searched for…”) and recommended links based on others’ searches.
* Ad hoc social networks. The community aspects of Shreveport were completely ad hoc, based only on search terms. No adding people as contacts or joining networks. Clearly this feature works better for populations with a strong shared vocabulary. (This is similar to what del.icio.us does with tags, but at the time it seemed much more radical.)
* Presence. The original Shreveport concept incorporated presence to encourage direct interaction between users.
One of the things I like about Shreveport is how it doesn’t require any new information. Not even tags. It leverages data that users already reveal–search terms and results selection.