Relevance odds of retrieval overlaps from seven search fields

Data contained in a 1982 paper were analyzed in terms of relevance odds of common items retrieved by searching any two content-bearing search fields. While the 1982 study compared the relative retrieval performance of 7 search fields, the present study shows that duplicate documents retrieved by the use of terms from any two of the fields would have higher odds of being judged relevant than those retrieved by only one of the fields. Sixty-three relevance odds were computed using the log cross product technique. The highest relevance odds were associated with common items retrieved from assigned descriptors and from truncated free-text terms from either the title or abstract fields; their relevance odds were 19 to 2 in favor of overlaps. Overlap retrieval could be considered a strategy for high precision searching.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31615/1/0000546.pd

Informetrics through Advanced Data Management. Complex Object Restructuring, Data Aggregation and Transitive Computation

This article considers how informetric calculations can easily and declaratively be specified through advanced data management techniques. In particular, bibliographic data and its modeling as complex objects (non-first normal form relations) as well as terminological and citation networks involving transitive relationships are considered. A very high-level declarative query interface, based on this data model, is introduced. The article demonstrates that such data modeling and query interface enable end-users to perform basic informetric ad hoc calculations, such as bibliographic coupling, author cocitation analysis, generalized impact factors, international visibility and international impact, productivity calculations in a given area, etc., easily and often with much less effort than in the contemporary online retrieval systems. Several fruitful generalizations of typical informetric measurements are also proposed. These are based on substituting traditional foci of analysis, e.g., journals, by other object types, such as authors, organizations, countries or classes of a classification scheme. It is shown that the proposed data modeling and query interface make it trivial to switch focus between various object types for informetric calculations. Moreover, it is demonstrated that all informetric data can easily be broken down by criteria that foster advanced analysis, e.g., by years or content-bearing attributes. Such modeling allows flexible data aggregation along many dimensions and the utilization of transitive relationships. These salient features emanate from the query interface’s general data restructuring and aggregation capabilities combined with transitive processing capabilities. The features are illustrated by means of sample queries and results