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In this article, we assess the effectiveness of Contextual Document Clustering (CDC) as a means of indexing within a dynamic and rapidly changing environment. We simulate a dynamic environment, by splitting two chronologically ordered datasets into time-ordered segments and assessing how the technique performs under two different scenarios. The first is when new documents are added incrementally without reclustering [incremental CDC (iCDC)], and the second is when reclustering is performed [nonincremental CDC (nCDC)]. The datasets are very large, are independent of each other, and belong to two very different domains. We show that CDC itself is effective at clustering very large document corpora, and that, significantly, it lends itself to a very simple, efficient incremental document addition process that is seen to be very stable over time despite the size of the corpus growing considerably. It was seen to be effective at incrementally clustering new documents even when the corpus grew to six times its original size. This is in contrast to what other researchers have found when applying similar simple incremental approaches to document clustering. The stability of iCDC is accounted for by the unique manner in which CDC discovers cluster themes. [ABSTRACT FROM AUTHOR]

In this report, we investigate how retrieving information can be improved through task-related indexing of documents based on ontologies. Different index types, varying from content-based keywords to structured task-based indexing ontologies are compared in an experiment that simulates the task of creating instructional material from a database of source material. To be able to judge the added value of task- and ontology-related indexes, traditional information retrieval performance measures are extended with new measures reflecting the quality of the material produced with the retrieved information. The results of the experiment show that a structured task-based indexing ontology improves the quality of the product created from retrieved material only to some extent, but that it certainly improves the efficiency and effectiveness of search and retrieval and precision of use. [ABSTRACT FROM AUTHOR]

Author self-citation has long been of interest to those working in informetrics for what it reveals about the publishing behavior of individuals and their relationships within academic networks. While this research has produced interesting insights, it typically assumes either that self-citation is a neutral form of reporting not unlike references to others' work or an unsavory kind of academic egotism. By examining self-citation in a wider context of self-mention, however, the phenomenon can be seen as part of a more comprehensive rhetorical strategy for emphasizing a writer's personal contribution to a piece of research and strengthening his or her knowledge claims, research credibility, and wider standing in the discipline. These meanings are not easily rein vealed through quantitative bibliometric methods and require careful text analyses and discourse-based interviews with academics. In this paper I explore the use of self-citation and authorial mention in a corpus of 240 research articles and 800 abstracts in eight disciplines. Through an analysis of these texts and interviews with expert informants I show how self-mention is used and the ways these uses reflect both the promotional strategies of individuals and the epistemological practices of their disciplines. [ABSTRACT FROM AUTHOR]

Part II. Investigates the level of communication in the indirect-collective referencing (ICR) phenomenon in the journal 'The Physical Review.' Analysis of ICR, a type of scientific referencing; Correlation of simple degree of documentedness with the frequency of ICR phenomenon on the journal; Demonstrations of ICR phenomenon in journals.