Search (5479 results, page 273 of 274)

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Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

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Abstract

The introduction and growth of the World Wide Web (WWW, or Web) have resulted in a profound change in the way individuals and organizations access information. In terms of volume, nature, and accessibility, the characteristics of electronic information are significantly different from those of even five or six years ago. Control of, and access to, this flood of information rely heavily an automated techniques for indexing and retrieval. According to Gudivada, Raghavan, Grosky, and Kasanagottu (1997, p. 58), "The ability to search and retrieve information from the Web efficiently and effectively is an enabling technology for realizing its full potential." Almost 93 percent of those surveyed consider the Web an "indispensable" Internet technology, second only to e-mail (Graphie, Visualization & Usability Center, 1998). Although there are other ways of locating information an the Web (browsing or following directory structures), 85 percent of users identify Web pages by means of a search engine (Graphie, Visualization & Usability Center, 1998). A more recent study conducted by the Stanford Institute for the Quantitative Study of Society confirms the finding that searching for information is second only to e-mail as an Internet activity (Nie & Ebring, 2000, online). In fact, Nie and Ebring conclude, "... the Internet today is a giant public library with a decidedly commercial tilt. The most widespread use of the Internet today is as an information search utility for products, travel, hobbies, and general information. Virtually all users interviewed responded that they engaged in one or more of these information gathering activities."
Techniques for automated indexing and information retrieval (IR) have been developed, tested, and refined over the past 40 years, and are well documented (see, for example, Agosti & Smeaton, 1996; BaezaYates & Ribeiro-Neto, 1999a; Frakes & Baeza-Yates, 1992; Korfhage, 1997; Salton, 1989; Witten, Moffat, & Bell, 1999). With the introduction of the Web, and the capability to index and retrieve via search engines, these techniques have been extended to a new environment. They have been adopted, altered, and in some Gases extended to include new methods. "In short, search engines are indispensable for searching the Web, they employ a variety of relatively advanced IR techniques, and there are some peculiar aspects of search engines that make searching the Web different than more conventional information retrieval" (Gordon & Pathak, 1999, p. 145). The environment for information retrieval an the World Wide Web differs from that of "conventional" information retrieval in a number of fundamental ways. The collection is very large and changes continuously, with pages being added, deleted, and altered. Wide variability between the size, structure, focus, quality, and usefulness of documents makes Web documents much more heterogeneous than a typical electronic document collection. The wide variety of document types includes images, video, audio, and scripts, as well as many different document languages. Duplication of documents and sites is common. Documents are interconnected through networks of hyperlinks. Because of the size and dynamic nature of the Web, preprocessing all documents requires considerable resources and is often not feasible, certainly not an the frequent basis required to ensure currency. Query length is usually much shorter than in other environments-only a few words-and user behavior differs from that in other environments. These differences make the Web a novel environment for information retrieval (Baeza-Yates & Ribeiro-Neto, 1999b; Bharat & Henzinger, 1998; Huang, 2000).

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Theme

Geschichte der Sacherschließung

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Theme

Geschichte der Sacherschließung

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Date

26.12.2011 14:08:22

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Content

"MOST INTEGRATED library systems, as they are currently configured and used, should be removed from public view. Before I say why, let me be clean that I think the integrated library system serves a very important, albeit limited, role. An integrated library system should serve as a key piece of the infrastructure of a library, handling such tasks as ma terials acquisition, cataloging (including holdings, of course), and circulation. The integrated library system should be a complete and accurate recording of a local library's holdings. It should not be presented to users as the primary system for locating information. It fails badly at that important job. - Lack of content- The central problem of almost any library catalog system is that it typically includes only information about the books and journals held by a parficular library. Most do not provide access to joumal article indexes, web search engines, or even selective web directories like the Librarians' Index to the Internet. If they do offen such access, it is only via links to these services. The library catalog is far from onestop shopping for information. Although we acknowledge that fact to each other, we still treat it as if it were the best place in the universe to begin a search. Most of us give the catalog a place of great prominente an our web pages. But Information for each book is limited to the author, title, and a few subject headings. Seldom can book reviews, jacket summaries, recommendations, or tables of contents be found-or anything at all to help users determine if they want the material. - Lack of coverage - Most catalogs do not allow patrons to discover even all the books that are available to them. If you're lucky, your catalog may cover the collections of those libraries with which you have close ties-such as a regional network. But that leaves out all those items that could be requested via interlibrary loan. As Steve Coffman pointed out in his "Building Earth's Largest Library" article, we must show our users the universe that is open to them, highlight the items most accessible, and provide an estimate of how long it would take to obtain other items. - Inability to increase coverage - Despite some well-meaning attempts to smash everything of interest into the library catalog, the fact remains that most integrated library systems expect MARC records and MARC records only. This means that whatever we want to put into the catalog must be described using MARC and AACR2 (see "Marc Must Die," LJ 10/15/02, p. 26ff.). This is a barrier to dramatically increasing the scope of a catalog system, even if we decided to do it. How would you, for example, use the Open Archives Initiative Harvesting Protocol to crawl the bibliographic records of remote repositories and make them searchable within your library catalog? It can't be dope, and it shouldn't. The library catalog should be a record of a given library's holdings. Period.
- User Interface hostility - Recently I used the Library catalogs of two public libraries, new products from two major library vendors. A link an one catalog said "Knowledge Portal," whatever that was supposed to mean. Clicking an it brought you to two choices: Z39.50 Bibliographic Sites and the World Wide Web. No public library user will have the faintest clue what Z39.50 is. The other catalog launched a Java applet that before long froze my web browser so badly I was forced to shut the program down. Pick a popular book and pretend you are a library patron. Choose three to five libraries at random from the lib web-cats site (pick catalogs that are not using your system) and attempt to find your book. Try as much as possible to see the system through the eyes of your patrons-a teenager, a retiree, or an older faculty member. You may not always like what you see. Now go back to your own system and try the same thing. - What should the public see? - Our users deserve an information system that helps them find all different kinds of resources-books, articles, web pages, working papers in institutional repositories-and gives them the tools to focus in an what they want. This is not, and should not be, the library catalog. It must communicate with the catalog, but it will also need to interface with other information systems, such as vendor databases and web search engines. What will such a tool look like? We are seeing the beginnings of such a tool in the current offerings of cross-database search tools from a few vendors (see "Cross-Database Search," LJ 10/15/01, p. 29ff). We are in the early stages of developing the kind of robust, userfriendly tool that will be required before we can pull our catalogs from public view. Meanwhile, we can begin by making what we have easier to understand and use."

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Abstract

This chapter examines the nature of semantic relations and their main applications in information science. The nature and types of semantic relations are discussed from the perspectives of linguistics and psychology. An overview of the semantic relations used in knowledge structures such as thesauri and ontologies is provided, as well as the main techniques used in the automatic extraction of semantic relations from text. The chapter then reviews the use of semantic relations in information extraction, information retrieval, question-answering, and automatic text summarization applications. Concepts and relations are the foundation of knowledge and thought. When we look at the world, we perceive not a mass of colors but objects to which we automatically assign category labels. Our perceptual system automatically segments the world into concepts and categories. Concepts are the building blocks of knowledge; relations act as the cement that links concepts into knowledge structures. We spend much of our lives identifying regular associations and relations between objects, events, and processes so that the world has an understandable structure and predictability. Our lives and work depend on the accuracy and richness of this knowledge structure and its web of relations. Relations are needed for reasoning and inferencing. Chaffin and Herrmann (1988b, p. 290) noted that "relations between ideas have long been viewed as basic to thought, language, comprehension, and memory." Aristotle's Metaphysics (Aristotle, 1961; McKeon, expounded on several types of relations. The majority of the 30 entries in a section of the Metaphysics known today as the Philosophical Lexicon referred to relations and attributes, including cause, part-whole, same and opposite, quality (i.e., attribute) and kind-of, and defined different types of each relation. Hume (1955) pointed out that there is a connection between successive ideas in our minds, even in our dreams, and that the introduction of an idea in our mind automatically recalls an associated idea. He argued that all the objects of human reasoning are divided into relations of ideas and matters of fact and that factual reasoning is founded on the cause-effect relation. His Treatise of Human Nature identified seven kinds of relations: resemblance, identity, relations of time and place, proportion in quantity or number, degrees in quality, contrariety, and causation. Mill (1974, pp. 989-1004) discoursed on several types of relations, claiming that all things are either feelings, substances, or attributes, and that attributes can be a quality (which belongs to one object) or a relation to other objects.
Linguists in the structuralist tradition (e.g., Lyons, 1977; Saussure, 1959) have asserted that concepts cannot be defined on their own but only in relation to other concepts. Semantic relations appear to reflect a logical structure in the fundamental nature of thought (Caplan & Herrmann, 1993). Green, Bean, and Myaeng (2002) noted that semantic relations play a critical role in how we represent knowledge psychologically, linguistically, and computationally, and that many systems of knowledge representation start with a basic distinction between entities and relations. Green (2001, p. 3) said that "relationships are involved as we combine simple entities to form more complex entities, as we compare entities, as we group entities, as one entity performs a process on another entity, and so forth. Indeed, many things that we might initially regard as basic and elemental are revealed upon further examination to involve internal structure, or in other words, internal relationships." Concepts and relations are often expressed in language and text. Language is used not just for communicating concepts and relations, but also for representing, storing, and reasoning with concepts and relations. We shall examine the nature of semantic relations from a linguistic and psychological perspective, with an emphasis on relations expressed in text. The usefulness of semantic relations in information science, especially in ontology construction, information extraction, information retrieval, question-answering, and text summarization is discussed. Research and development in information science have focused on concepts and terms, but the focus will increasingly shift to the identification, processing, and management of relations to achieve greater effectiveness and refinement in information science techniques. Previous chapters in ARIST on natural language processing (Chowdhury, 2003), text mining (Trybula, 1999), information retrieval and the philosophy of language (Blair, 2003), and query expansion (Efthimiadis, 1996) provide a background for this discussion, as semantic relations are an important part of these applications.

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Abstract

The image as a new indexing resource to be integrated to the information systems, must be studied with the final purpose of representing its contents according to the special characteristics it exhibits. Differences between the traditional documents and the singularities of digital audiovisual information that is substituting analogical information, are being researched. Another aspect being examined is the re-evaluation of the thesaurus and the convenience of its use in the new informative environment. It has been proposed an image analysis extrapolated from the Panofsky's proposal to analyse art works and, therefore, foresee the representation of the different elements necessary for the audiovisual document analysis in the thesaurus to be built. 1. Introduction The human being is exposed to a constant exercise with unreal images, taking into account television, computers, publicity at the streets and in the movies. Sixteen out of the twenty four hours of the day, he's submitted to images that try to reproduce the real world. When sleeping there's also image activity, dreams occur with images and imagination is accompanied by a representation with these ones: we imagine situations, solutions and actions. There's even the proposal that man's memory is stored in our brain in the form of images. The evolution of the intellect, and together with it, that of the visual- perceptive process, leads the man to develop an exceptional skill: that one of generating representations that "imitate" objects and scenes of the environment. (Yankelevich, 1993, 15-31) The traditional photograph-illustrated document is being substituted in part by the audiovisual one, that nowadays has been transformed from analogical to digital systems, converting images, sound, music and voice in manipulable and feasible-to-transform data and intercalating them to generate another type of product, different from the original. Videos, movies, sound, texts and graphics are digital substances expressed in data. This characteristic of the digital information takes us back to many menhires and dolmens from the Stone Age, used by the Celtic druids to register their formulas and enchantings (it is said that the stones they used came from the Stone Age but the most accepted tendency affirms that these inscriptions dated from the Christian Era); also to take notes employing the alphabet known as Ogham, that originated from Ogma, the Celtic God of Writing. (Rosaspini, 1998, p. 180)

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Abstract

1. Introduction Theoretical context independent explanations of classification could enhance the universality of classification research and make knowledge about classification available to settings other than traditional libraries. There is a tremendous need for constructing classificatory structures in a range of settings many of which are far removed from the environment in which classification theory and research has been practiced in the last century and a half. The construction of classificatory structures an the Internet, intranets, and in knowledge management systems has received some attention lately. The question examined here is whether it is possible to create a single theory of classification that applies to the range of contexts in which classificatory structures are applied. The object of this paper is to question the assumption that bibliographic classification theory can resemble scientific theories. It is argued that the context of any classification influences the use and understanding of the classification to such a degree that the classification cannot be understood separate from its context. Furthermore, the development from being a novice classifier or classificationist to becoming an expert is explored. lt is assumed scientific theories must relate as much to the activity of novices as to the activity of experts and that scientific theories explain both what it is that novices do and what experts do. It is argued that expertise is achieved not through a correct application of a classification theory but through experiences and adjustment to a particular context and that the activities of novices are quite distinct from the activities of experts in that experts draws an the context of the situation and that novices do not. 2. Theory of Classification Langridge (1976) provides an account of the principles of constructing knowledge organization systems and the theoretical underpinnings of different approaches. He identifies four principles that have guided construction of knowledge organization systems: 1) ideological, 2) social purpose, 3) scientific, and 4) the disciplines. The ideological principle organizes knowledge according to an ideology that the knowledge organization system serves. Langridge gives the examples of "the Christian schemes of the Middle Ages and the Soviet scheme which substitutes for the Bible and Christianity the works of Marx and Lenin and the 'religion' of communism" (Langridge, 1976, p. 4-5).

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Abstract

Special classifications have been somewhat neglected in KO compared to general classifications. The methodology of constructing special classifications is important, however, also for the methodology of constructing general classification schemes. The methodology of constructing special classifications can be regarded as one among about a dozen approaches to domain analysis. The methodology of (special) classification in LIS has been dominated by the rationalistic facet-analytic tradition, which, however, neglects the question of the empirical basis of classification. The empirical basis is much better grasped by, for example, bibliometric methods. Even the combination of rational and empirical methods is insufficient. This presentation will provide evidence for the necessity of historical and pragmatic methods for the methodology of classification and will point to the necessity of analyzing "paradigms". The presentation covers the methods of constructing classifications from Ranganathan to the design of ontologies in computer science and further to the recent "paradigm shift" in classification research. 1. Introduction Classification of a subject field is one among about eleven approaches to analyzing a domain that are specific for information science and in my opinion define the special competencies of information specialists (Hjoerland, 2002a). Classification and knowledge organization are commonly regarded as core qualifications of librarians and information specialists. Seen from this perspective one expects a firm methodological basis for the field. This paper tries to explore the state-of-the-art conceming the methodology of classification. 2. Classification: Science or non-science? As it is part of the curriculum at universities and subject in scientific journals and conferences like ISKO, orte expects classification/knowledge organization to be a scientific or scholarly activity and a scientific field. However, very often when information specialists classify or index documents and when they revise classification system, the methods seem to be rather ad hoc. Research libraries or scientific databases may employ people with adequate subject knowledge. When information scientists construct or evaluate systems, they very often elicit the knowledge from "experts" (Hjorland, 2002b, p. 260). Mostly no specific arguments are provided for the specific decisions in these processes.

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Abstract

There have been various approaches to conceptualizing interactive information retrieval (IR), which can be generally divided into system and user approaches (Hearst, 1999; cf. also Spink, 1997). Both system and user approaches define user-system interaction in terms of the system and the user reacting to the actions or behaviors of the other: the system reacts to the user's input; the user to the output of the system (Spink, 1997). In system approach models of the interaction, e.g., Moran (1981), "[T]he user initiates an action or operation and the system responds in some way which in turn leads the user to initiate another action and so on" (Beaulieu, 2000, p. 433). In its purest form, the system approach models the user as a reactive part of the interaction, with the system taking the lead (Bates, 1990). User approaches, on the other hand, in their purest form wish to insert a model of the user in all its socio-cognitive dimensions, to the extent that system designers consider such approaches impractical (Vakkari and Jarvelin, 2005, Chap. 7, this volume). The cognitive approach to IR interaction attempts to overcome this divide (Ruthven, 2005, Chap. 4, this volume; Vakkari and Jarvelin, 2005 Chap. 7, this volume) by representing the cognitive elements of both system designers and the user in the interaction model (Larsen and Ingwersen, 2005 Chap. 3, this volume). There are cognitive approach researchers meeting in a central ground from both the system and user side. On the system side, are computer scientists employing cognitive research to design more effective IR systems from the point of view of the user's task (Nathan, 1990; Fischer, Henninger, and Redmiles, 1991; O'Day and Jeffries, 1993; Russell et al., 1993; Kitajima and Polson, 1996; Terwilliger and Polson, 1997). On the user side are cognitive approach researchers applying methods, concepts and models from psychology to design systems that are more in tune with how users acquire information (e.g., Belkin, 1980; Ford (2005, Chap. 5, this volume); Ingwersen (Larsen and Ingwersen, 2005, Chap. 3, this volume); Saracevic, 1996; Vakkari (Vakkari and Jarvelin, 2005, Chap. 7, this volume)).

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