Wednesday, August 8, 2007

Clustering with Search Engines

When I first read about the Clustering, I was confused about its utility and ability to work on limited set of search results. But over the period time, after reading lot of research material on search usability and taking to people, I realized that searcher do not go beyond few pages. In fact the study shows that 2/3 of searcher do not go beyond 2 pages of 10 results each. The searcher either find the information that they are looking for or change the search terms. I personally do not go beyond 2-3 pages unless I am not able to refined search phrase. Even with 2 pages of result set, users have filter and infer the context of search results to find for the relevant information that they are looking for. So actually the users are spending more time on search result windows rather than actually working on searched information. When I am searching, it is not only important how relevant the search results are, but also how much time it took to me to get to those results. Here I see value of clustering with search engines.

Search technology has been evolving and maturing over last few years. The search companies are completing with each other for creating a niche for themselves and attracting more traffic to get benefit from advertising, but ever increasing demand of end users are always overtaking them from behind. The users are getting interested in federated search, clustering and faceted search apart from the regular sequential search. Google web search provides clustering as indented search results when it find more search results from same site or site section. Some other search engines like Vivisimo Velocity provide Topic Clustering, or grouping results into topics/subjects, that help in refine searches.

Can we use clustering for anything else? We can use clustering to build applications like job sites, event sites, social networking etc. Also we can generate tag cloud to guide users navigate through popular topics. The list can grow as we see more need for applications.

I was working with Nutch and Google search appliance, when I got interested in the clustering and faceted search technologies. I wanted to integrate the clustering technology with both these search engines to show my clients the value of clustering technology. I gave them demo with Clusty web search and they see lot of value. But question was, can I integrate it with Google search appliance and is there any free or low cost tool that can provide the same functionality. I knew about Vivisimo, but client wanted a cheaper solution, so I started digging more in the open source arena.

Then I came across Carrot2, Open Source Search Results Clustering Engine. Search Carrot2 provides an architecture for acquiring search results from various sources (YahooAPI, GoogleAPI, MSNAPI, eTools Meta Search, Alexa Web Search, PubMed, OpenSearch, Lucene index, SOLR), clustering the results and visualising the clusters. Currently, 5 clustering algorithms are available that are suitable for different kinds of document clustering tasks. Carrot2 has been successfully used in a number of commercial and research applications and resulted in a number of interesting publications.

I found this tool interesting and wanted to use it with my existing search engines. The tool provides seamless integration with nutch and lucene search engines. The developer only needs to point to existing search indexes and customize the page layout. The carrot application is deployed as webapp which you can be drop in any web application server. The deployment was cake walk and results were fascinating. Then I also got it working with the Google search appliance. Here I had to use its Java APIs to build a clustered search interface from the results of Google appliance.

If anyone is looking for low cost clustering solution, one can use open source clustering engine which can be integrated with any existing web search engines and also with enterprise search engines like Google search appliance, lucene index (one can debate on its enterprise capability). It is easy to deploy and configure and does not impose any extra baggage.

I am sure Google must be working on this technology and would come with a solution which is a notch better than Vivisimo or Carrot2. I am eagerly waiting to hear from them.


Anonymous said...

Have you done any testing from performance point of you on carrot2. Do post some results if yes.

Ravi Govil said...

Yes, We are currently doing testing on Carrot2. The fact is the performance delay is more on getting the search results from search engine and less in getting clustered results from Carrot2. Performance also depends on how many research results you are feeding to Carrot2.

Anonymous said...

SearchBlox has released its latest 4.1 version which includes clustered search results using carrot2. They have a Free edition for download.