Comparing FAST and Google Search Appliance is like comparing is like comparing Oracle Databases to Microsoft Access. ok . And I will tell you why. FAST not only returns a black box relevancy we provide an open platform that gives you the full flexibility to connect to limitless repositories, enrich content as it is fed into the engine, manage and define the entire search experience for multiple groups of users. Furthermore, because FAST ESP is a true platform we can create multi-purpose applications and not just plug in a point solution.
In saying that, it is possible to keep it simple as Google. but on top of this, we provide richer and more comprehensive management tools and also a richer and more effective user experience.
So we have determined and implement what is required to provide a Google like experience. Because let's face it, we all use Google everyday and it works well. However, we have further innovated beyond this point to what we call Search 2.0, how can we improve over a simply dumping a list of text links in front of the user.
To illustrate with an analogy, let's pretend there is a property agency called Google properties. They are a brick and mortar property agency, but they operate in a similar way to the Google search engine.
So, we call into this agency in search for information on a properties. So we go in and ask them for information on all the properties in a particular area, lets say Hampsted. Now, rather than asking any questions to disambiguate what exactly you mean by properties in Hampsted they say, I just have what you are looking for and pull out a several thousand page directory listing everything they know on properties in Hampsted and dumping it on the table in front of you without asking any further questions. They then ask you to flick through the different pages to find what you are looking for.
This is the search box, keyword, text link paradigm made famous by our good friends at Google.
Now, apply the FAST ESP model to this scenario. In this case the agent is the FAST search engine:
The agent firstly disambiguates the customer's query by breaking it into different categories.
Is it property for purchase, rent or to sell? By asking this question the agent/engine can quickly narrow the possible results by discarding irrelevant categories. This enables the customer to start understanding what exactly it is she requires because we do not always know that as we commence the query. By suggesting information through tag clouds and category dividers we can guide the user down the path to answers.
Let us now say that the customer elects to purchase property. We can now narrow the result set and utilize dynamically generated facets to further guide the customer. In this example, we could ask the customer questions such as:
What is your budget?
What type of property - apartment, bungalow, house?
How many bedrooms?
How many bathrooms?
And so on.
These questions are essentially the guided navigators that the FAST engine provides alongside the results set. They act as questions that further refine the result set as the user steps through.
Furthermore, because FAST can interact with the content as it is being ingested we can begin to extract the key concepts, words and entities mentioned in the document. At results processing time we can present these items extracted from the underlying result set alongside the list of links. They essentially act as a "table of contents" over the results set. They mention the key elements of the under lying results and selecting them direct consumers to the relevant content. This is useful when the user is 'Discovering' an area for the first time. The extracted entities and words give a quick overview of what areas pertain to the query term.
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