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The paper introduces bibliometrics to the research area of knowledge organization – more precisely in relation to construction and maintenance of thesauri. As such, the paper reviews related work that has been of inspiration for the assembly of a semi‐automatic, bibliometric‐based, approach for construction and maintenance. Similarly, the paper discusses the methodical considerations behind the approach. Eventually, the semi‐automatic approach is used to verify the applicability of bibliometric methods as a supplement to construction and maintenance of thesauri. In the context of knowledge organization, the paper outlines two fundamental approaches to knowledge organization, that is, the manual intellectual approach and the automatic algorithmic approach. Bibliometric methods belong to the automatic algorithmic approach, though bibliometrics do have special characteristics that are substantially different from other methods within this approach.

The purpose of this paper is to explore query expansion via conceptual distance in thesaurus indexed collections

An extract of the National Museum of Science and Industry's collections database, indexed with the Getty Art and Architecture Thesaurus (AAT), was the dataset for the research. The system architecture and algorithms for semantic closeness and the matching function are outlined. Standalone and web interfaces are described and formative qualitative user studies are discussed. One user session is discussed in detail, together with a scenario based on a related public inquiry. Findings are set in context of the literature on thesaurus‐based query expansion. This paper discusses the potential of query expansion techniques using the semantic relationships in a faceted thesaurus.

Thesaurus‐assisted retrieval systems have potential for multi‐concept descriptors, permitting very precise queries and indexing. However, indexer and searcher may differ in terminology judgments and there may not be any exactly matching results. The integration of semantic closeness in the matching function permits ranked results for multi‐concept queries in thesaurus‐indexed applications. An in‐memory representation of the thesaurus semantic network allows a combination of automatic and interactive control of expansion and control of expansion on individual query terms.

The application of semantic expansion to browsing may be useful in interface options where thesaurus structure is hidden.

This paper aims to report on an empirical case study, (single case multi‐site) employing both a “hard” and “soft” method. The tangible, visible component of the study was the production of a database whose fields were to be the source of tacit knowledge emergence.

The proposition was that the possibility for the capture of tacit knowledge was subject to four conditions. The first was the need for a teleological motive and purpose. The second was a bounded environment expressed in this case in terms of the published corporate goals and key business drivers. The third was the production of a controlled vocabulary that made sense to both the respondents in the context of the true nature of the business activity. The fourth and most important condition was the interactive and iterative process that allowed those involved to own the tacit knowledge emerging process.

Results supported the idea that under bounded conditions, a shared sense of purpose and an iterative process where ownership was possible, tacit knowledge could be captured. In the bounded environment tacit knowledge was found to be not haphazard, confirming its “end purpose” for being.

The findings of the research have practical application for organisations wishing to capture the tacit knowledge of their knowledge workers and describes a methodology for emerging and capturing it.

Is of value in presenting a method for emerging tacit knowledge in‐play in a bounded environment.

The purpose of this paper is to examine the role of warrant in daily classification design in general and in negotiating disparate classification goals in particular.

This paper synthesizes classification research on forms of warrant and uses examples of classification decisions from ethnographic engagement with designers to illustrate how forms of warrant interact in daily classification decisions.

Different forms of warrant, though associated with incompatible theories of classification design, coexist in daily classification decisions. A secondary warrant might be employed to augment the primary warrant of a system, such as to decide among equally valid terms, or to overturn a decision based on the primary warrant, such as when ethical impacts are prioritized above user preference.

This paper calls for empirical research using the application of warrant as an object of analysis.

The paper connects a ubiquitous and observable element of classification design – the application of warrant – to longstanding divisions in classification theory. This paper demonstrates how the analysis of daily classification design can illuminate the interaction between disparate philosophies of classification.

To propose a comprehensive and semi‐automatic method for constructing or updating knowledge organization tools such as thesauri.

The paper proposes a comprehensive methodology for thesaurus construction and maintenance combining shallow NLP with a clustering algorithm and an information visualization interface. The resulting system TermWatch, extracts terms from a text collection, mines semantic relations between them using complementary linguistic approaches and clusters terms using these semantic relations. The clusters are mapped onto a 2D using an integrated visualization tool.

The clusters formed exhibit the different relations necessary to populate a thesaurus or ontology: synonymy, generic/specific and relatedness. The clusters represent, for a given term, its closest neighbours in terms of semantic relations.

This could change the way in which information professionals (librarians and documentalists) undertake knowledge organization tasks. TermWatch can be useful either as a starting point for grasping the conceptual organization of knowledge in a huge text collection without having to read the texts, then actually serving as a suggestive tool for populating different hierarchies of a thesaurus or an ontology because its clusters are based on semantic relations.

This lies in several points: combined use of linguistic relations with an adapted clustering algorithm, which is scalable and can handle sparse data. The paper proposes a comprehensive approach to semantic relations acquisition whereas existing studies often use one or two approaches. The domain knowledge maps produced by the system represents an added advantage over existing approaches to automatic thesaurus construction in that clusters are formed using semantic relations between domain terms. Thus while offering a meaningful synthesis of the information contained in the original corpus through clustering, the results can be used for knowledge organization tasks (thesaurus building and ontology population) The system also constitutes a platform for performing several knowledge‐oriented tasks like science and technology watch, textmining, query refinement.

With the growing recognition that thesauri aid information retrieval, organisations are beginning to adopt, and in many cases, create thesauri. This paper offers some guidance on the construction process.

An opinion piece with a practical focus, based on recent experiences gleaned from consultancy work.

A number of steps can be taken to ensure any thesaurus under construction is fit for purpose. Due consideration is therefore given to aspects such as term selection, structure and notation, thesauri standards, software and Web display issues, thesauri evaluation and maintenance. This paper also notes that creating new subject schemes from scratch, however attractive, contributes to the plethora of terminologies currently in existence and can limit user searching within particular contexts. The decision to create a “new” thesaurus should therefore be taken carefully and observance of standards is paramount.

This paper offers advice to assist practitioners in the development of thesauri.

Useful guidance for those practitioners new to the area of thesaurus construction is provided, together with an overview of selected key processes involved in the construction of a thesaurus.

To avoid confusion, I will start by saying that I intend to use the word ‘user’ in a different contest to that in which it has been used by Dr Matthews and other speakers. Previous speakers have discussed problems of organizations such as ICI, Shell and UKCIS who are interested in operating magnetic tape services. They have therefore considered the user as the organization operating the magnetic tape service. However, the users whom I will be discussing are the individual research scientists for whom a profile is written, who receives a list of titles or abstracts, and who in some cases goes to the actual documents and possibly extracts useful information from those documents. I have some doubts, however, whether the discussion of the two types of user in the same meeting is a reasonable combination as my own comments will obviously be from a rather different point of view to that of previous speakers.

Recently, the importance and effectiveness of Wikipedia Mining has been shown in several researches. One popular research area on Wikipedia Mining focuses on semantic relatedness measurement, and research in this area has shown that Wikipedia can be used for semantic relatedness measurement. However, previous methods are facing two problems; accuracy and scalability. To solve these problems, the purpose of this paper is to propose an efficient semantic relatedness measurement method that leverages global statistical information of Wikipedia. Furthermore, a new test collection is constructed based on Wikipedia concepts for evaluating semantic relatedness measurement methods.

The authors' approach leverages global statistical information of the whole Wikipedia to compute semantic relatedness among concepts (disambiguated terms) by analyzing co‐occurrences of link pairs in all Wikipedia articles. In Wikipedia, an article represents a concept and a link to another article represents a semantic relation between these two concepts. Thus, the co‐occurrence of a link pair indicates the relatedness of a concept pair. Furthermore, the authors propose an integration method with tfidf as an improved method to additionally leverage local information in an article. Besides, for constructing a new test collection, the authors select a large number of concepts from Wikipedia. The relatedness of these concepts is judged by human test subjects.

An experiment was conducted for evaluating calculation cost and accuracy of each method. The experimental results show that the calculation cost of this approach is very low compared to one of the previous methods and more accurate than all previous methods for computing semantic relatedness.

This is the first proposal of co‐occurrence analysis of Wikipedia links for semantic relatedness measurement. The authors show that this approach is effective to measure semantic relatedness among concepts regarding calculation cost and accuracy. The findings may be useful to researchers who are interested in knowledge extraction, as well as ontology researches.

A brief discussion of discipline formation in information management is used to introduce the way different terminology is employed for describing information professionals as well as what it is that they do. This leads to a comparison of how information professionals and their professions are described in several of the thesauri that are the tools of the trade. These thesauri show marked differences in treatment of similar concepts.