Search (316 results, page 1 of 16)

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Abstract

Investigates current thinking on the theory and application of index language. Explains their links with on-line retrieval systems and the need to go beyond a narrow library application, identifying 2 regularly occurring points of view: transferring traditional ideas about conventional keyword catalogues to post-coordinate on-line searches and redundant terminology about input and its replacement by pure subject searching. Explores the general subject literature, the theory of verbal documentation languages, syntactical indexing, the thesaurus principle and faceted classification structure

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Footnote

Rez. in: JASIST 54(2003) no.7, S.695-697 (R. Savolainen): "Donald O. Case has written an ambitious book to create an overall picture of the major approaches to information needs and seeking (INS) studies. The aim to write an extensive review is reflected in the list of references containing about 700 items. The high ambitions are explained an p. 14, where Case states that he is aiming at a multidisciplinary understanding of the concept of information seeking. In the Preface, the author characterizes his book as an introduction to the topic for students at the graduate level, as well as as a review and handbook for scholars engagged in information behavior research. In my view, Looking for Information is particularly welcome as an academic textbook because the field of INS studies suffers from the lack of monographs. Along with the continuous growth of the number of journal articles and conference papers, there is a genuine need for a book that picks up the numerous pieces and puts them together. The use of the study as a textbook is facilitated by clearly delineated sections an major themes and the wealth of concrete examples of information seeking in everyday contexts. The book is lucidly written and it is accessible to novice readers, too. At first glance, the idea of providing a comprehensive review of INS studies may seem a mission impossible because the current number of articles, papers, and other contributions in this field is nearing the 10,000 range (p. 224). Donald Case is not alone in the task of coming to grips with an increasing number of studies; similar problems have been faced by those writing INS-related chapters for the Annual Review of Information Science and Technology (ARIST). Case has solved the problem of "too many publications to be reviewed" by concentrating an the INS literature published during the last two decades. Secondly, studies an library use and information retrieval are discussed only to a limited extent. In addition, Case is highly selective as to studies focusing an the use of specific sources and channels such as WWW. These delineations are reasonable, even though they beg some questions. First, how should one draw the line between studies an information seeking and information retrieval? Case does not discuss this question in greater detail, although in recent years, the overlapping areas of information seeking and retrieval studies have been broadened, along with the growing importance of WWW in information seeking/retrieval. Secondly, how can one define the concept of information searching (or, more specifically, Internet or Web searching) in relation to information seeking and information retrieval? In the field of Web searching studies, there is an increasing number of contributions that are of direct relevance to information-seeking studies. Clearly, the advent of the Internet, particularly, the Web, has blurred the previous lines between INS and IR literature, making them less clear cut. The book consists of five main sections, and comprises 13 chapters. There is an Appendix serving the needs of an INS textbook (questions for discussion and application). The structure of the book is meticulously planned and, as a whole, it offers a sufficiently balanced contribution to theoretical, methodological, and empirical issues of INS. The title, Looking for Information: A Survey of Research an Information Seeking, Needs, and Behavior aptly describes the main substance of the book. . . . It is easy to agree with Case about the significance of the problem of specialization and fragmentation. This problem seems to be concomitant with the broadening field of INS research. In itself, Case's book can be interpreted as a struggle against this fragmentation. His book suggests that this struggle is not hopeless and that it is still possible to draw an overall picture of the evolving research field. The major pieces of the puzzle were found and the book will provide a useful overview of INS studies for many years."

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Abstract

State of the art review of the historical development of information science as deemed to be covered by the particular interests of memebers of the American Society for Information Science, as defined as the representation, storage, transmission, selection, retrieval, filtering, and use of documents and messages. Arranges the references cited roughly according to the classification scheme used by Information Science Abstracts, and so uses the headings: background; information science; techniques and technology; information related behaviour; application areas; social aspects; education for information science; institutions; individuals; geographical areas; and conclusions

Date

13. 6.1996 19:22:20

Source

Annual review of information science and technology. 30(1995), S.385-416

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Abstract

Natural Language Processing (NLP) is an area of research and application that explores how computers can be used to understand and manipulate natural language text or speech to do useful things. NLP researchers aim to gather knowledge an how human beings understand and use language so that appropriate tools and techniques can be developed to make computer systems understand and manipulate natural languages to perform desired tasks. The foundations of NLP lie in a number of disciplines, namely, computer and information sciences, linguistics, mathematics, electrical and electronic engineering, artificial intelligence and robotics, and psychology. Applications of NLP include a number of fields of study, such as machine translation, natural language text processing and summarization, user interfaces, multilingual and cross-language information retrieval (CLIR), speech recognition, artificial intelligence, and expert systems. One important application area that is relatively new and has not been covered in previous ARIST chapters an NLP relates to the proliferation of the World Wide Web and digital libraries.

Source

Annual review of information science and technology. 37(2003), S.51-90

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Abstract

Identifies the interest in questions of classified catalogues generated by the development of on-line catalogues, establishing a difference between 2 large areas: free access to information items in a systematic arrangement and expressing the contents of books by means of notational symbols in a classification system in a local catalogue. Examines the elements and structure of classification systems, the internationally important universal classifications, the procedures for book display and systematic processing in West German public libraries and exhibtion techniques in West German academic libraries. Covers universal and faceted classifications, as well as classification systems in on-line catalogues

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Abstract

Knowledge Organization Systems, even traditional ones, such as the Universal Decimal Classification, have been studied to improve the retrieval of information online, although the potential of using knowledge structures in the user interface has not yet been widespread. Objective: This study presents a mapping of scientific production on information retrieval methodologies, which make use of the Universal Decimal Classification. Methodology: Systematic Literature Review, conducted in two stages, with a selection of 44 publications, resulting in the time interval from 1964 to 2017, whose categories analyzed were: most productive authors, languages of publications, types of document, year of publication, most cited work, major impact journal, and thematic categories covered in the publications. Results: A total of nine more productive authors and co-authors were found; predominance of the English language (42 publications); works published in the format of journal articles (33); and highlight to the year 2007 (eight publications). In addition, it was identified that the most cited work was by Mcilwaine (1997), with 61 citations, and the journal Extensions & Corrections to the UDC was the one with the largest number of publications, in addition to the incidence of the theme Universal Automation linked to a thesaurus for information retrieval, present in 19 works. Conclusions: Shortage of studies that explore the potential of the Decimal Classification, especially in Brazilian literature, which highlights the need for further study on the topic, involving research at the national and international levels.

Footnote

Englischer Titel: Use of the Universal Decimal Classification for the recoery of information in digital environments: a systematic review of literature.

Theme

Klassifikationssysteme im Online-Retrieval

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Date

22. 1.2012 13:01:26

Source

Annual review of information science and technology. 42(2008), S.3-42

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Source

Annual review of information science and technology. 22(1987), S.109-145

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Source

Annual review of information science and technology. 22(1987), S.41-77

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Abstract

This review describes experimental designs (users, search tasks, measures, etc.) used by 31 controlled user studies of information visualization (IV) tools for textual information retrieval (IR) and a meta-analysis of the reported statistical effects. Comparable experimental designs allow research designers to compare their results with other reports, and support the development of experimentally verified design guidelines concerning which IV techniques are better suited to which types of IR tasks. The studies generally use a within-subject design with 15 or more undergraduate students performing browsing to known-item tasks on sets of at least 1,000 full-text articles or Web pages on topics of general interest/news. Results of the meta-analysis (N = 8) showed no significant effects of the IV tool as compared with a text-only equivalent, but the set shows great variability suggesting an inadequate basis of comparison. Experimental design recommendations are provided which would support comparison of existing IV tools for IR usability testing.

Source

Journal of the American Society for Information Science and Technology. 59(2008) no.6, S.1012-1024

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Abstract

State of the art review of natural language processing updating an earlier review published in ARIST 22(1987). Discusses important developments that have allowed for significant advances in the field of natural language processing: materials and resources; knowledge based systems and statistical approaches; and a strong emphasis on evaluation. Reviews some natural language processing applications and common problems still awaiting solution. Considers closely related applications such as language generation and th egeneration phase of machine translation which face the same problems as natural language processing. Covers natural language methodologies for information retrieval only briefly

Source

Annual review of information science and technology. 31(1996), S.83-119

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Abstract

Points out that expert systems have great potential to enhance access to information retrieval systems as they use expertise to carry out tasks such as diagnosis and planning and make expertise available to nonexperts. Potential end users of online information retrieval systems are frequently deterred by the complexity of theses systems. Expert systems can mediate between the searcher and the information retrieval system and might be the key both to increasing and end user searching and to improving the quality of searches overall

Source

Annual review of information science and technology. 26(1991), S.113-154

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Abstract

Information retrieval - the retrieval, primarily, of documents or textual material - is fundamentally a linguistic process. At the very least we must describe what we want and match that description with descriptions of the information that is available to us. Furthermore, when we describe what we want, we must mean something by that description. This is a deceptively simple act, but such linguistic events have been the grist for philosophical analysis since Aristotle. Although there are complexities involved in referring to authors, document types, or other categories of information retrieval context, here I wish to focus an one of the most problematic activities in information retrieval: the description of the intellectual content of information items. And even though I take information retrieval to involve the description and retrieval of written text, what I say here is applicable to any information item whose intellectual content can be described for retrieval-books, documents, images, audio clips, video clips, scientific specimens, engineering schematics, and so forth. For convenience, though, I will refer only to the description and retrieval of documents. The description of intellectual content can go wrong in many obvious ways. We may describe what we want incorrectly; we may describe it correctly but in such general terms that its description is useless for retrieval; or we may describe what we want correctly, but misinterpret the descriptions of available information, and thereby match our description of what we want incorrectly. From a linguistic point of view, we can be misunderstood in the process of retrieval in many ways. Because the philosophy of language deals specifically with how we are understood and mis-understood, it should have some use for understanding the process of description in information retrieval. First, however, let us examine more closely the kinds of misunderstandings that can occur in information retrieval. We use language in searching for information in two principal ways. We use it to describe what we want and to discriminate what we want from other information that is available to us but that we do not want. Description and discrimination together articulate the goals of the information search process; they also delineate the two principal ways in which language can fail us in this process. Van Rijsbergen (1979) was the first to make this distinction, calling them "representation" and "discrimination.""

Source

Annual review of information science and technology. 37(2003), S.3-50

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Abstract

State of the art review exploring the problem of bibliographic citations to resources that exist only in electronic form where the cited items may no longer be locatable at the URL indicated. Notes that the Internet is currently in a state of near chaos in terms of access and organization, while searching, usually performed with word based search engines, is generally not adequate for the needs of most users. Reviews strategies used by librarians for cataloguing and classifying information resources on the Internet. Techniques used include: automatic classification projects and classified subject trees, like the BUBL Subject Tree; CyberDewey, and the WWW Virtual Library. Considers OPAC like library catalogues such as the UK's CATRIONA Project and OCLC's InterCat. Explores retrieval tools used with concept analysis and other non traditional proposals, which include some library expertise, usually the use of one of the major library classifications. Pays particular attention to the UDC

Source

Annual review of information science and technology. 31(1996), S.189-219

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Abstract

Gives an annual review of literature dealing with CD-ROMs for 1993. The first section covers developments in the industry including: the current state of the art; developments in Europe, Canada, and other regions; hardware; CD-R; Kodak Photo CD; other formats; and multimedia. The second section deals with the library amrket discussing: managing CD-ROM; selection; instruction; libraries as CD-ROM publishers; use in elementary and school libraries and government libraries and the third world; and networking. Looks to future developments

Source

Computers in libraries. 14(1994) no.8, S.43-55

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Abstract

State of the art review of methods available for accessing collections of digital images by means of manual and automatic indexing. Distinguishes between concept based indexing, in which images and the objects represented, are manually identified and described in terms of what they are and represent, and content based indexing, in which features of images (such as colours) are automatically identified and extracted. The main discussion is arranged in 6 sections: studies of image systems and their use; approaches to indexing images; image attributes; concept based indexing; content based indexing; and browsing in image retrieval. The performance of current image retrieval systems is largely untested and they still lack an extensive history and tradition of evaluation and standards for assessing performance. Concludes that there is a significant amount of research to be done before image retrieval systems can reach the state of development of text retrieval systems

Source

Annual review of information science and technology. 32(1997), S.169-196

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Abstract

Discusses the human-computer interface for information retrieval and notes that research on human-computer interface design has generated many widely-accepted principles of interface design which should be of interest and value to designers of information retrieval systems. Work on display features such as highlighting, colour, icons, and windows has received considerable attention. research has also focused on how the user interacts with the system, whether by commands, menus, or direct manipulation. Studies of interfaces for information retrieval systems reveal that online searching has emphasised developments of front ends, with some novel uses of graphics. CD-ROM and optical media are characterised by interface diversity, again with some inclusion of graphic interfaces. Online catalogues and full text data bases have provided interesting comparisons of mode of interaction

Source

Annual review of information science and technology. 26(1991), S.155-195

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Abstract

Latent Semantic Analysis (LSA) was first introduced in Dumais, Furnas, Landauer, and Deerwester (1988) and Deerwester, Dumais, Furnas, Landauer, and Harshman (1990) as a technique for improving information retrieval. The key insight in LSA was to reduce the dimensionality of the information retrieval problem. Most approaches to retrieving information depend an a lexical match between words in the user's query and those in documents. Indeed, this lexical matching is the way that the popular Web and enterprise search engines work. Such systems are, however, far from ideal. We are all aware of the tremendous amount of irrelevant information that is retrieved when searching. We also fail to find much of the existing relevant material. LSA was designed to address these retrieval problems, using dimension reduction techniques. Fundamental characteristics of human word usage underlie these retrieval failures. People use a wide variety of words to describe the same object or concept (synonymy). Furnas, Landauer, Gomez, and Dumais (1987) showed that people generate the same keyword to describe well-known objects only 20 percent of the time. Poor agreement was also observed in studies of inter-indexer consistency (e.g., Chan, 1989; Tarr & Borko, 1974) in the generation of search terms (e.g., Fidel, 1985; Bates, 1986), and in the generation of hypertext links (Furner, Ellis, & Willett, 1999). Because searchers and authors often use different words, relevant materials are missed. Someone looking for documents an "human-computer interaction" will not find articles that use only the phrase "man-machine studies" or "human factors." People also use the same word to refer to different things (polysemy). Words like "saturn," "jaguar," or "chip" have several different meanings. A short query like "saturn" will thus return many irrelevant documents. The query "Saturn Gar" will return fewer irrelevant items, but it will miss some documents that use only the terms "Saturn automobile." In searching, there is a constant tension between being overly specific and missing relevant information, and being more general and returning irrelevant information.
A number of approaches have been developed in information retrieval to address the problems caused by the variability in word usage. Stemming is a popular technique used to normalize some kinds of surface-level variability by converting words to their morphological root. For example, the words "retrieve," "retrieval," "retrieved," and "retrieving" would all be converted to their root form, "retrieve." The root form is used for both document and query processing. Stemming sometimes helps retrieval, although not much (Harman, 1991; Hull, 1996). And, it does not address Gases where related words are not morphologically related (e.g., physician and doctor). Controlled vocabularies have also been used to limit variability by requiring that query and index terms belong to a pre-defined set of terms. Documents are indexed by a specified or authorized list of subject headings or index terms, called the controlled vocabulary. Library of Congress Subject Headings, Medical Subject Headings, Association for Computing Machinery (ACM) keywords, and Yellow Pages headings are examples of controlled vocabularies. If searchers can find the right controlled vocabulary terms, they do not have to think of all the morphologically related or synonymous terms that authors might have used. However, assigning controlled vocabulary terms in a consistent and thorough manner is a time-consuming and usually manual process. A good deal of research has been published about the effectiveness of controlled vocabulary indexing compared to full text indexing (e.g., Bates, 1998; Lancaster, 1986; Svenonius, 1986). The combination of both full text and controlled vocabularies is often better than either alone, although the size of the advantage is variable (Lancaster, 1986; Markey, Atherton, & Newton, 1982; Srinivasan, 1996). Richer thesauri have also been used to provide synonyms, generalizations, and specializations of users' search terms (see Srinivasan, 1992, for a review). Controlled vocabularies and thesaurus entries can be generated either manually or by the automatic analysis of large collections of texts.
With the advent of large-scale collections of full text, statistical approaches are being used more and more to analyze the relationships among terms and documents. LSA takes this approach. LSA induces knowledge about the meanings of documents and words by analyzing large collections of texts. The approach simultaneously models the relationships among documents based an their constituent words, and the relationships between words based an their occurrence in documents. By using fewer dimensions for representation than there are unique words, LSA induces similarities among terms that are useful in solving the information retrieval problems described earlier. LSA is a fully automatic statistical approach to extracting relations among words by means of their contexts of use in documents, passages, or sentences. It makes no use of natural language processing techniques for analyzing morphological, syntactic, or semantic relations. Nor does it use humanly constructed resources like dictionaries, thesauri, lexical reference systems (e.g., WordNet), semantic networks, or other knowledge representations. Its only input is large amounts of texts. LSA is an unsupervised learning technique. It starts with a large collection of texts, builds a term-document matrix, and tries to uncover some similarity structures that are useful for information retrieval and related text-analysis problems. Several recent ARIST chapters have focused an text mining and discovery (Benoit, 2002; Solomon, 2002; Trybula, 2000). These chapters provide complementary coverage of the field of text analysis.

Source

Annual review of information science and technology. 38(2004), S.189-230

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Abstract

Social media has become integrated into the fabric of the scholarly communication system in fundamental ways, principally through scholarly use of social media platforms and the promotion of new indicators on the basis of interactions with these platforms. Research and scholarship in this area has accelerated since the coining and subsequent advocacy for altmetrics-that is, research indicators based on social media activity. This review provides an extensive account of the state-of-the art in both scholarly use of social media and altmetrics. The review consists of 2 main parts: the first examines the use of social media in academia, reviewing the various functions these platforms have in the scholarly communication process and the factors that affect this use. The second part reviews empirical studies of altmetrics, discussing the various interpretations of altmetrics, data collection and methodological limitations, and differences according to platform. The review ends with a critical discussion of the implications of this transformation in the scholarly communication system.

Source

Journal of the Association for Information Science and Technology. 68(2017) no.9, S.2037-2062