Abstract
Information retrieval (IR) is about making systems for finding documents or information. Knowledge organization (KO) is the field concerned with indexing, classification, and representing documents for IR, browsing, and related processes, whether performed by humans or computers. The field of IR is today dominated by search engines like Google. An important difference between KO and IR as research fields is that KO attempts to reflect knowledge as depicted by contemporary scholarship, in contrast to IR, which is based on, for example, “match” techniques, popularity measures or personalization principles. The classification of documents in KO mostly aims at reflecting the classification of knowledge in the sciences. Books about birds, for example, mostly reflect (or aim at reflecting) how birds are classified in ornithology. KO therefore requires access to the adequate subject knowledge; however, this is often characterized by disagreements. At the deepest layer, such disagreements are based on philosophical issues best characterized as “paradigms”. No IR technology and no system of knowledge organization can ever be neutral in relation to paradigmatic conflicts, and therefore such philosophical problems represent the basis for the study of IR and KO.
Highlights
IntroductionInformation retrieval (IR) and knowledge organization (KO) are two research fields that, on the one hand, are separate fields of study, but on the other hand, have the same aim: to facilitate the findability of documents, knowledge, and information
Anderson and Pérez-Carballo’s [1] handbook of Knowledge organization (KO) has the title Information Retrieval Design, which indicates the close connection between KO and Information retrieval (IR), where IR is about search processes, while KO is about designing optimal structures for IR
Looking at the principle underlying Google’s search engine, we find that four main principles are (a) “exact match”, (b) “best match”, (c) popularity measures, and (d) personalization
Summary
Information retrieval (IR) and knowledge organization (KO) are two research fields that, on the one hand, are separate fields of study, but on the other hand, have the same aim: to facilitate the findability of documents, knowledge, and information. To claim that since only the individual user knows their own “information need”, they are the only person qualified to set principles of what should be found in IR and how documents should be indexed or classified This is the view underlying user-oriented and cognitive approaches in information science and KO and is discussed a little in the present article and more detailed in [9]. We consider a thought experiment of searching for cities in Sweden and here it is claimed that the relevant information may be found in a map or gazetteer constructed by some experts, not what the user believes are Swedish cities Both the “systems approach” and the “user approach” (as well as the dichotomy itself) are problematic positions, and a third way is needed. A third way is the domain analytical approach [12], according to which both human information needs and technological approaches are understood as influenced by the understanding and background knowledge of the actors (including the computer programmers and mediators), which is shaped by the social and disciplinary contexts, the traditions, and the paradigms in which the actors have been socialized
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