After much anticipation an amazing new Patent retrieval tool launched yesterday. SparkIP is an amazing new patent search tool of which my colleague (he is my boss-man really) Tim Lenoir is a founder. SparkIP combines the robust on-the-fly clustering of search results similar to Vivisimo’s Clusty but with a pretty incredible twist. The search engine results are navigated by the user in a visual way. Results are clustered, and first the user is presented not with patent results per se but rather with patent cluster results. The company refers to each cluster as a “SparkCluster Map.” Each of these cluster “maps” have numerous clusters within them. This set of cluster maps (shown here)


referred to as a landscape, is an excellent and robust way of reducing often-overwhelmingly-sized relevant document results while providing complex visual information about each cluster. This is truly a forward-looking tool in many respects but particularly in terms of generating intelligent and useful information about technologies, people, and institutions related to a keyword search. SparkIP has raised the bar on information retrieval right here. But your search is not done yet.

Given the landscape you can then select any of the specific cluster maps (seven in all were returned on “text mining”) by clicking directly on the map graphic. I selected the second cluster map, “information retrieval.” This then brings an enlarged view of the cluster map revealing the clusters within the map, shown here:


Then clicking onto one of the map nodes/clusters (I selected the “document information retrieval” node at the very center of the cluster map) you see a view called “Technology Detail” (shown below):


More information-overload-reducing brilliance on display here in SparkIP. First, note that while 61 patents were retrieved, only 10 were returned. Further, there are likely hundreds more patents relevant to “text mining.” What appears to be happening here is that SparkIP has developed patent-filtering heuristics “under the hood” that get rid of the high volume of junk patents cluttering any patent database. After all, many if not most patents are created by their originators for purposes other than to stake a claim on a highly specific technology. Many a business game is played with patents as the pieces. An organization might want to try and occupy an intellectual property space to see if it can land licensing suckers. Other patents are premature. Some others overreach or are incredibly vague and therefore unenforceable. And so on.

There are a number of small problems with the interface as with many a beta product. The back buttom removes you entirely from your search results rather than helping you navigate backwards from, say, technology detail view to cluster map view. The meaning of visual iconography such as cluster map node size or color, while intuitive, are not altogether clear just from naively using the tool.

But wait folks, that’s not all. In addition to keyword-to-landscape patent search SparkIP will also open up an eBay-esque marketplace for intellectual property. I don’t know of that part is already live or not. I hope to have more time to play around with the site in the coming days.

SparkIP was founded at Duke University through collaboration between Dr. Lenoir, current Pratt School of Engineering Dean Rob Clark, and John Hopkins Provost and Senior President of Academic Affairs Kristina Johnson. Since joining Lenoir at Duke I’ve had a couple of small windows of opportunity to provide some technical advice on cluster metrics with SparkIP engineer (and founder) Kevin Webb. But I never even got to see a demo of this thing. And let me tell you, man, this thing is amazing. I put this tool right up there with Clusty and the TRIP evidence-based medicine site as a retrieval tool among the best since the arrival of Google beta.

Congratulations to you Tim, and to you Kevin, and to the rest of the SparkIP team.