A useful whitepaper by Marc Krellenstein, CTO at Lucid Imagination.
I am interested in your reaction to Marc’s listing of the use cases for full-text searching:
Full-text search is good at a variety of information requests that can be hard to satisfy with other technologies. These include:
- Finding the most relevant information about a specific topic, or an answer to a particular question,
- Locating a specific document or content item, and
- Exploring information in a general area, or even browsing the collection of documents or other content as a whole (this is often supported by clustering; see below).
For my class, do a “reaction” of one page in length giving your reaction to each of these points (that’s 3 pages total), and what “other” technologies might you use?
For class discussion, it would be nice if you can offer an example of either full-text searching meeting the requests or “other” technologies meeting these requests.
Testing/exploring Marc’s “information requests:”
Two teams.
Team One has a set of the Great Books of the Western World and use the the Syntopicon to answer information requests.
Team Two has access to a full-text version of Great Books of the Western World to answer information requests.
The class, including the teams, creates questions that are sent to me privately and I will prepare the final list of questions to be submitted by the teams. Questions are given to both teams at the same time and the first team with the correct answer (must have citation in the Great Books) wins.
I am open to suggestions for prizes.
The class following the contest we will discuss why some questions were better for full-text and why some worked better with the Syntopicon. It will give you insight into the choices you will have to make when creating a topic map.
BTW, the requirements section of Marc’s paper will help you in designing any information system. If you don’t know what is expected and can’t test for it, you are unlikely to satisfy anyone’s needs.