Relevancy

In general, customers need to strike a balance between finding everything related to a query and only the documents that relate to a given query.

The truth, The whole truth [Recall] (For a researcher) and nothing but the truth[Precision] (for a fact finder).

Recall is the ratio of the number of relevant records retrieved to the total number of relevant records in the index. knowledge discovery or compliance applications will rate recall as being more important than precision – in other words, customers do not want to “miss” any important documents.

Apple – recall : all docs that mention apple precision: type apple computers, only docs mentioning apple computers and not the fruit

RECALL: Increasing the findability. Amplify the target size.

PRECISION: Removing spurious results. Returning nothing but the truth.

Precision is the ratio of the number of relevant records retrieved to the total number of irrelevant and relevant records retrieved.
But in an e-commerce or e-directory environment, users prefer much more precise search results so that customers are not swamped with too many non-specific results.

Search users do [not all share the same] business objects and in turn do not have the same search needs. As a result we do not entertain the BLACK BOX APPROACH to search that our competitors do.

Google search for ”Caring for my Jaguar” will bring back the same results irrespective of whether I am a car owner or a zoo keeper.

It is a one – size fits all approach to search relevancy.

Relevancy is also a balance between RECALL and PRECISION.

VISUALISE A GRAPHIC EQUALIZER ON AN EIGHTIES SOUND SYSTEM WE CAN INCREASE/DECREASE THE DIALS FOR EACH OF THESE.

JUST AS WE HAVE PRESETS – THINK ROCK, JAZZ, CLASSIC .

WE SIMILARLY HAVE PRESETS FOR NEWSPAPER, YELLOW PAGES, INTRANET – IT DEPT, SALES DEPT