Emerging as a discipline in the first half of the twentieth century, the information sciences study how people, groups, organizations, and governments create, share, disseminate, manage, search, ...access, evaluate, and protect information, as well as how different technologies and policies can facilitate and constrain these activities. Given the broad span of the information sciences, it is perhaps not surprising that there is no consensus regarding its underlying theory—the purposes of it, the types of it, or how one goes about developing new theories to talk about new research questions. Diane H. Sonnenwald and the contributors to this volume seek to shed light on these issues by sharing reflections on the theory-development process. These reflections are not meant to revolve around data collection and analysis; rather, they focus on the struggles, challenges, successes, and excitement of developing theories. The particular theories that the contributors explore in their essays range widely, from theories of literacy and reading to theories of design and digital search. Several chapters engage with theories of the behavior of individuals and groups; some deal with processes of evaluation; others reflect on questions of design; and the rest treat cultural and scientific heritage. The ultimate goal, Sonnenwald writes in her introduction, is to “encourage, inspire, and assist individuals striving to develop and/or teach theory development."
Purpose - To show that stem generation compares well with lemmatization as a morphological tool for a highly inflectional language for IR purposes in a best-match retrieval system.Design methodology ...approach - Effects of three different morphological methods - lemmatization, stemming and stem production - for Finnish are compared in a probabilistic IR environment (INQUERY). Evaluation is done using a four-point relevance scale which is partitioned differently in different test settings.Findings - Results show that stem production, a lighter method than morphological lemmatization, compares well with lemmatization in a best-match IR environment. Differences in performance between stem production and lemmatization are small and they are not statistically significant in most of the tested settings. It is also shown that hitherto a rather neglected method of morphological processing for Finnish, stemming, performs reasonably well although the stemmer used - a Porter stemmer implementation - is far from optimal for a morphologically complex language like Finnish. In another series of tests, the effects of compound splitting and derivational expansion of queries are tested.Practical implications - Usefulness of morphological lemmatization and stem generation for IR purposes can be estimated with many factors. On the average P-R level they seem to behave very close to each other in a probabilistic IR system. Thus, the choice of the used method with highly inflectional languages needs to be estimated along other dimensions too.Originality value - Results are achieved using Finnish as an example of a highly inflectional language. The results are of interest for anyone who is interested in processing of morphological variation of a highly inflected language for IR purposes.
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