Continuing with the competency of information-seeking strategies within varying databases, this post discusses using the "Most Specific Facet First" strategy as it might be done within the LexisNexis database.
This search model is described in the text Information representation and retrieval in the digital age (Chu, 2007) as "efficient" because the searcher begins with "the term that should take the least amount of time to be processed" and because "there would be no point to continue the search if the number of results retrieved ... seems unacceptable" (i.e. too small a return). (p. 86)
For this post I continue with the previous search query which follows the theme of this blog: What are some of the things being done in academic libraries to implement Library 2.0?
As identified in the previous post, the concepts within this query could be expressed as:
Library 2.0
academic libraries
("Implementation" for this search purpose is more of a delimiter or a descriptor rather than a search concept.)
Often the searcher can identify the most specific or least prolific concept, the one that will return the fewest hits from a database. Since I'm using LexisNext for this experiment, I am going to assume that the concept "Library 2.0" is the most specific of the concepts. (LexisNexis is described as "a full-text resource for news, business, legal research, medical information and reference," according to the Texas Woman's University database description.)
Just to verify my assumption, I do quick searches within LexisNexis (Major U.S. and World Publications only) on the single concepts by themselves, and I find these numbers for results: Library 2.0 - returns 595 possibly relevant information sources; 
academic libraries - 999 returns (maximum number)
So indeed, the first concept would be my most specific facet. (Click on the image to view the search and returns more clearly.)
Reflection: The ideal situation for a effective and efficient Specific Facet search would be to begin with a concept that would take little time to be processed and which would return an acceptable number of results. However a return of 595 hits, as in my case with the term "Library 2.0," is still too broad to be an effective search. Thus this particular search model indicates that I would need to continue my search using another model, one which would allow me to narrow my hits with a second or third concept. For the specific query with which I began, this has proven to be an ineffective search model.
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