Efficiency and effectiveness of deep structure based subject indexing languages: PRECIS vs. DSIS
2010-11-22T11:19:14Z (GMT) by
A 'Subject Indexing Language' (SIL) is an artificial language used for formulating names of subjects. Although classificationists have sought for universals in many fields of study such as, philosophy, biology, general systems theory, etc., the search for a deep structure of SILs formally began with Ranganathan's idea of 'absolute syntax' and was brought to the present by G. Bhattacharyya and D. Austin. Whereas Bhattacharyya's deep structure of SIL is primarily based on classificatory principles (parallel to 'absolute syntax'), the deep structure proposed by Austin has a linguistic connotation. The present study describes and compares two such deep structurebased SILs, viz., PRECIS (PREserved Context Index System) and DSIS (Deep Structure Indexing System), a recent computerized version of POPSI (POstulate-based Permuted Subject Indexing), developed by F. J. Devadason at Documentation Research and Training Centre, Bangalore, India. Both also belong to the category of SILs typified as 'string indexing' languages. The study involves: i) writing of a suitable DSIS index entry generation program, ii) using both PRECIS (in-house) and DSIS programs to index a collection of representative sample documents from the soft sciences, iii) analyzing and comparing their respective syntactic and semantic aspects in terms of both linguistic and classificatory principles, and iv) applying some measures of efficiency and effectiveness. It was realized that certain modifications in the existing DSIS string manipulation algorithms are necessary to make the program fully operational. Although, no attempts have been made to quantify the measures of effectiveness and efficiency as such, suggestions have been provided as to what these probably would be. Some indications of their searching difficulties for a prospective searcher have been put forward as well.