Tag Archives: Search appliance

Google Search Appliance (GSA) 6.10 released

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Last week, Google released version 6.10 of the software to their Google Search Appliance (GSA).

This is a minor update and the focus at the Google teams has been bug fixes and increased stability. Looking at the release notes, there’s indeed plenty of bugs that has been solved.

However, there are also some new features in this release. Some of the more interesting, in my opinion, are:

Multiple front-end configuration for Dynamic Navigation

Since the 6.8 release, the GSA has been able to provde facets, or Dynamic Navigation as Google calls it. However the facets has been global so you couldn’t have two front ends with different facets. This is now possible.
More feeds statistics and Adjust PageRank in feeds
More statistics of what’s happening with feeds you push into the GSA is a very welcome feature. The possibility to adjus PageRank allows for some more control over relevancy in feeds.

Indexing Crawl time kerberos support and Indexing large files

Google is working hard on security and every release since 6.0 has included some security improvements. Nice to see that it continues. Since beginning, the GSA has simply dropped files bigger than 30 MB. Now it will index larger (you can configure how large), but still only the first 2.5 MB of the content will be indexed.

Stopword lists for differented languages

Scalability Centralized configuration

For a multi-node GSA setup, you can now specify the configuration on the master and it’s propagated to the slaves

For a complete list of new features, see the New and Changed Features page in the documentation

Google Search Appliance Learns What You Want to Find

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Analyzing user behaviour is a key ingredient to make a search solutions successful. By using Search Analytics, you gain knowledge of how your users use the search solution and what they expect to find. With this knowledge, simple adjustments such as Key Matches, Synonyms and Query Suggestion can enhance the findability of your search solution.

In addition to this, you can also tune the relevancy by knowing what your users are after. An exciting field in this area is to automate this task, i.e by analyzing what users click on in the search result, the relevancy of the documents it automatically adjusted. Findwise has been looking into this area lately, but there hasn’t been any out-of-the-box functionality for this from any vendor.

Until now.

Two weeks ago Google announced the second major upgrade this year for the Google Search Appliance. Labeled as version 6.2, it brings a lot of new features. The most interesting and innovative one is the Self-Learning Scorer. The self learning scorer analyzes user’s click and behaviour in the search result and use it as input to adjust the relevancy. This means that if a lot of people clicks on the third result, the GSA will boost this document to appear higher up in the result set. So, without you having to do anything, the relevance will increase over time making your Search Solution perform better the more it is used. It’s easy to imagine this will create an upward spiral.

The 6.2 release also delivers improvements regarding security, connectivity, indexing overview and more. To read more about the release, head over to the Google Enterprise Blog.