One of the central themes surrounding the Implicit Web is the power of the electronic footprint.
Wherever we go, we leave footprints. In the real world, these are quickly washed away by erosion and other natural forces. The electronic world, however, is far, far different: footprints often never disappear. Every move we make online, every bit of information we post, every web link we click, can be recorded.
The Implicit Web is about leveraging this automatically-recorded data to achieve new and useful goals.
One area that’s particularly exciting to me is the utility provided by merging implicit data collection/analysis and automatic information retrieval.
Neat stuff! I love the idea of “re-searching” automatically, leveraging an Internet user’s original search query.
A few days ago I decided to mess around with this “re-search” idea and ended up with something that I’ve been calling “pre-search.”
Pre-search is the concept of preemptive search, or retrieving information before a user asks for it (or even knows to ask). This idea can be of particular use with blogs and other topical information sources.
I created two basic pre-search mashups for Feedburner-enabled blogs, using the Feedburner FeedFlare API:
Both of these are pretty straightforward, doing the following:
1. For every blog post, use the Yahoo Terms Extraction API to gather ‘key terms’ from the post title.
3. Formulate the top three results into a clickable link and show them below the blog post.
This results in the automatic display of related content for a given blog post, using a combination of content analysis (on the blog post title) and information retrieval (Lijit/Google Blog Search).