Search (263 results, page 1 of 14)

  • × theme_ss:"Literaturübersicht"
  1. Belkin, N.J.; Croft, W.B.: Retrieval techniques (1987) 0.11
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    Source
    Annual review of information science and technology. 22(1987), S.109-145
  2. Hawkins, D.T.: On-line information retrieval bibliography : 1965-1976 (1977) 0.09
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  3. Gödert, W.: Klassifikatorische Inhaltserschließung : Ein Übersichtsartikel als kommentierter Literaturbericht (1990) 0.08
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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
  4. Buckland, M.K.; Liu, Z.: History of information science (1995) 0.07
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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
  5. McGill, M.J.; Huitfeldt, J.: Experimental techniques of information retrieval (1979) 0.07
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    Source
    Annual review of information science and technology. 14(1979), S.93-128
  6. Kantor, P.B.: Information retrieval techniques (1994) 0.05
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    Abstract
    State of the art review of information retrieval techniques viewed in terms of the growing effort to implement concept based retrieval in content based algorithms. Identifies trends in the automation of indexing, retrieval, and the interaction between systems and users. Identifies 3 central issues: ways in which systems describe documents for purposes of information retrieval; ways in which systems compute the degree of match between a given document and the current state of the query; amd what the systems do with the information that they obtain from the users. Looks at information retrieval techniques in terms of: location, navigation; indexing; documents; queries; structures; concepts; matching documents to queries; restoring query structure; algorithms and content versus concepts; formulation of concepts in terms of contents; formulation of concepts with the assistance of the users; complex system codes versus underlying principles; and system evaluation
    Imprint
    Medford, NJ : Learned Information Inc.
    Source
    Annual review of information science and technology. 29(1994), S.53-90
  7. Robertson, S.E.: Theories and models in information retrieval (1977) 0.05
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    Abstract
    This paper is concerned with recent work in the theory of information retrieval. More particularly, it is concerned with theories which tackle the problem of retrieval performance, in a sense which will be explained. The aim is not an exhaustive survey of such work; rather it is an analysis and synthesis of those contributions which I feel to be important or find interesting
  8. Smith, L.C.: Artificial intelligence and information retrieval (1987) 0.04
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    Source
    Annual review of information science and technology. 22(1987), S.41-77
  9. Börner, K.; Chen, C.; Boyack, K.W.: Visualizing knowledge domains (2002) 0.04
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    Abstract
    This chapter reviews visualization techniques that can be used to map the ever-growing domain structure of scientific disciplines and to support information retrieval and classification. In contrast to the comprehensive surveys conducted in traditional fashion by Howard White and Katherine McCain (1997, 1998), this survey not only reviews emerging techniques in interactive data analysis and information visualization, but also depicts the bibliographical structure of the field itself. The chapter starts by reviewing the history of knowledge domain visualization. We then present a general process flow for the visualization of knowledge domains and explain commonly used techniques. In order to visualize the domain reviewed by this chapter, we introduce a bibliographic data set of considerable size, which includes articles from the citation analysis, bibliometrics, semantics, and visualization literatures. Using tutorial style, we then apply various algorithms to demonstrate the visualization effectsl produced by different approaches and compare the results. The domain visualizations reveal the relationships within and between the four fields that together constitute the focus of this chapter. We conclude with a general discussion of research possibilities. Painting a "big picture" of scientific knowledge has long been desirable for a variety of reasons. Traditional approaches are brute forcescholars must sort through mountains of literature to perceive the outlines of their field. Obviously, this is time-consuming, difficult to replicate, and entails subjective judgments. The task is enormously complex. Sifting through recently published documents to find those that will later be recognized as important is labor intensive. Traditional approaches struggle to keep up with the pace of information growth. In multidisciplinary fields of study it is especially difficult to maintain an overview of literature dynamics. Painting the big picture of an everevolving scientific discipline is akin to the situation described in the widely known Indian legend about the blind men and the elephant. As the story goes, six blind men were trying to find out what an elephant looked like. They touched different parts of the elephant and quickly jumped to their conclusions. The one touching the body said it must be like a wall; the one touching the tail said it was like a snake; the one touching the legs said it was like a tree trunk, and so forth. But science does not stand still; the steady stream of new scientific literature creates a continuously changing structure. The resulting disappearance, fusion, and emergence of research areas add another twist to the tale-it is as if the elephant is running and dynamically changing its shape. Domain visualization, an emerging field of study, is in a similar situation. Relevant literature is spread across disciplines that have traditionally had few connections. Researchers examining the domain from a particular discipline cannot possibly have an adequate understanding of the whole. As noted by White and McCain (1997), the new generation of information scientists is technically driven in its efforts to visualize scientific disciplines. However, limited progress has been made in terms of connecting pioneers' theories and practices with the potentialities of today's enabling technologies. If the difference between past and present generations lies in the power of available technologies, what they have in common is the ultimate goal-to reveal the development of scientific knowledge.
    Source
    Annual review of information science and technology. 37(2003), S.179-258
  10. Enser, P.G.B.: Visual image retrieval (2008) 0.04
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    Date
    22. 1.2012 13:01:26
    Source
    Annual review of information science and technology. 42(2008), S.3-42
  11. Mostafa, J.: Digital image representation and access (1994) 0.04
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    Abstract
    State of the art review of techniques used to generate, store and retrieval digital images. Explains basic terms and concepts related to image representation and describes the differences between bilevel, greyscale, and colour images. Introduces additional image related data, specifically colour standards, correction values, resolution parameters and lookup tables. Illustrates the use of data compression techniques and various image data formats that have been used. Identifies 4 branches of imaging research related to dtaa indexing and modelling: verbal indexing; visual surrogates; image indexing; and data structures. Concludes with a discussion of the state of the art in networking technology with consideration of image distribution, local system requirements and data integrity
    Imprint
    Medford, NJ : Learned Information Inc.
    Source
    Annual review of information science and technology. 29(1994), S.91-135
  12. Gödert, W.: Verbale Inhaltserschließung : Ein Übersichtsartikel als kommentierter Literaturbericht (1991) 0.04
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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
  13. Sugar, W.: User-centered perspective of information retrieval research and analysis methods (1995) 0.04
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    Abstract
    Presents a state of the art review of the underlying theories of and analysis methods used to study the ways in which users (end users) receive and interpret information through information retrieval systems and looks at the potential for refining theories and adopting new analysis methods. Focuses on approaches that advocate the user centred perspective, including: the cognitive approach; and the holistic approach. Identifies and summarizes the significant studies and ideas since 1986 that are represented by these approaches and looks toward the design of more effective systems that are user oriented and incorporate features such as filtering that would provide retrieval results based on individual or group preferences. Concludes that systems designed from the user centred perspective would not only serve the intended audience but would further the user centred perspective of the entire information retrieval discipline
    Source
    Annual review of information science and technology. 30(1995), S.77-109
  14. Rasmussen, E.M.: Indexing and retrieval for the Web (2002) 0.04
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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).
    Source
    Annual review of information science and technology. 37(2003), S.91-126
  15. Julien, C.-A.; Leide, J.E.; Bouthillier, F.: Controlled user evaluations of information visualization interfaces for text retrieval : literature review and meta-analysis (2008) 0.03
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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
  16. Looking for information : a survey on research on information seeking, needs, and behavior (2016) 0.03
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    Abstract
    The 4th edition of this popular and well-cited text is now co-authored, and includes significant changes from earlier texts. Presenting a comprehensive review of over a century of research on information behavior (IB), this book is intended for students in information studies and disciplines interested in research on information activities. The initial two chapters introduce IB as a multi-disciplinary topic, the 3rd provides a brief history of research on information seeking. Chapter four discusses what is meant by the terms "information" and "knowledge. "Chapter five discusses "information needs," and how they are addressed. The 6th chapter identifies many related concepts. Twelve models of information behavior (expanded from earlier editions) are illustrated in chapter seven. Chapter eight reviews various paradigms and theories informing IB research. Chapter nine examines research methods invoked in IB studies and a discussion of qualitative and mixed approaches. The 10th chapter gives examples of IB studies by context. The final chapter looks at strengths and weaknesses, recent trends, and future development.
    RSWK
    Information Retrieval
    Series
    Studies in information
    Subject
    Information Retrieval
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  17. Woodward, J.: Cataloging and classifying information resources on the Internet (1996) 0.03
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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
  18. Chowdhury, G.G.: Natural language processing (2002) 0.03
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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
  19. Case, D.O.: Looking for information : a survey on research on information seeking, needs, and behavior (2002) 0.03
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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."
    Series
    Library and information science
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  20. Dumais, S.T.: Latent semantic analysis (2003) 0.03
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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

Languages

  • e 252
  • d 7
  • m 1
  • pt 1
  • ru 1
  • sp 1
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Types

  • a 233
  • b 34
  • m 18
  • s 7
  • el 5
  • r 2
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