Search (94 results, page 1 of 5)

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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.

Source

Annual review of information science and technology. 40(2006), S.157-228

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Abstract

The concept of information as we use it in everyday English, in the sense of knowledge communicated, plays a central role in contemporary society. The development and widespread use of computer networks since the end of World War II, and the emergence of information science as a discipline in the 1950s, are evidence of this focus. Although knowledge and its communication are basic phenomena of every human society, it is the rise of information technology and its global impacts that characterize ours as an information society. It is commonplace to consider information as a basic condition for economic development together with capital, labor, and raw material; but what makes information especially significant at present is its digital nature. The impact of information technology an the natural and social sciences in particular has made this everyday notion a highly controversial concept. Claude Shannon's (1948) "A Mathematical Theory of Communication" is a landmark work, referring to the common use of information with its semantic and pragmatic dimensions, while at the same time redefining the concept within an engineering framework. The fact that the concept of knowledge communication has been designated by the word information seems, prima facie, a linguistic happenstance. For a science like information science (IS), it is of course important how fundamental terms are defined; and in IS, as in other fields, the question of how to define information is often raised. This chapter is an attempt to review the status of the concept of information in IS, with reference also to interdisciplinary trends. In scientific discourse, theoretical concepts are not true or false elements or glimpses of some element of reality; rather, they are constructions designed to do a job in the best possible way. Different conceptions of fundamental terms like information are thus more or less fruitful, depending an the theories (and in the end, the practical actions) they are expected to support. In the opening section, we discuss the problem of defining terms from the perspective of the philosophy of science. The history of a word provides us with anecdotes that are tangential to the concept itself. But in our case, the use of the word information points to a specific perspective from which the concept of knowledge communication has been defined. This perspective includes such characteristics as novelty and relevante; i.e., it refers to the process of knowledge transformation, and particularly to selection and interpretation within a specific context. The discussion leads to the questions of why and when this meaning was designated with the word information. We will explore this history, and we believe that our results may help readers better understand the complexity of the concept with regard to its scientific definitions.
Discussions about the concept of information in other disciplines are very important for IS because many theories and approaches in IS have their origins elsewhere (see the section "Information as an Interdisciplinary Concept" in this chapter). The epistemological concept of information brings into play nonhuman information processes, particularly in physics and biology. And vice versa: the psychic and sociological processes of selection and interpretation may be considered using objective parameters, leaving aside the semantic dimension, or more precisely, by considering objective or situational parameters of interpretation. This concept can be illustrated also in physical terms with regard to release mechanisms, as we suggest. Our overview of the concept of information in the natural sciences as well as in the humanities and social sciences cannot hope to be comprehensive. In most cases, we can refer only to fragments of theories. However, the reader may wish to follow the leads provided in the bibliography. Readers interested primarily in information science may derive most benefit from the section an "Information in Information Science," in which we offer a detailed explanation of diverse views and theories of information within our field; supplementing the recent ARIST chapter by Cornelius (2002). We show that the introduction of the concept of information circa 1950 to the domain of special librarianship and documentation has in itself had serious consequences for the types of knowledge and theories developed in our field. The important question is not only what meaning we give the term in IS, but also how it relates to other basic terms, such as documents, texts, and knowledge. Starting with an objectivist view from the world of information theory and cybernetics, information science has turned to the phenomena of relevance and interpretation as basic aspects of the concept of information. This change is in no way a turn to a subjectivist theory, but an appraisal of different perspectives that may determine in a particular context what is being considered as informative, be it a "thing" (Buckland, 1991b) or a document. Different concepts of information within information science reflect tensions between a subjective and an objective approach. The concept of interpretation or selection may be considered to be the bridge between these two poles. It is important, however, to consider the different professions involved with the interpretation and selection of knowledge. The most important thing in IS (as in information policy) is to consider information as a constitutive forte in society and, thus, recognize the teleological nature of information systems and services (Braman, 1989).

Source

Annual review of information science and technology. 37(2003), S.343-411

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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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Date

22. 1.2012 13:01:26

Source

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

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Date

13. 7.2008 9:30:22

Source

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

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Date

13. 7.2008 19:22:28

Source

Annual review of information science and technology. 40(2006), S.xxx-xxx

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Date

13. 7.2008 19:53:22

Source

Annual review of information science and technology. 41(2007), S.xxx-xxx

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Abstract

This paper reviews the enormous changes in cataloging and classification reflected in the literature of 2003 and 2004, and discusses major themes and issues. Traditional cataloging and classification tools have been re-vamped and new resources have emerged. Most notable themes are: the continuing influence of the Functional Requirements for Bibliographic Control (FRBR); the struggle to understand the ever-broadening concept of an "information entity"; steady developments in metadata-encoding standards; and the globalization of information systems, including multilinguistic challenges.

Date

10. 9.2000 17:38:22

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Abstract

The challenge of cataloging Web sites and electronic resources was the most important issue facing the cataloging world in the last year. This article reviews attempts to analyze and revise the cataloging code in view of the new electronic environment. The difficulties of applying traditional library cataloging standards to Web resources has led some to favor metadata as the best means of providing access to these materials. The appropriate education and training for library cataloging personnel remains crucial during this transitional period. Articles on user understanding of Library of Congress subject headings and on cataloging practice are also reviewed.

Date

10. 9.2000 17:38:22

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Abstract

This paper reviews library literature on cataloging and classification published in 2005-06. It covers pertinent literature in the following areas: the future of cataloging; Functional Requirement for Bibliographic Records (FRBR); metadata and its applications and relation to Machine-Readable Cataloging (MARC); cataloging tools and standards; authority control; and recruitment, training, and the changing role of catalogers.

Date

10. 9.2000 17:38:22

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Abstract

The purpose of this selected bibliography is to introduce issues and problems in relation to thesaurus construction and to present a set of readings that may be used in practical thesaurus design. The concept of thesaurus is discussed, the purpose of the thesaurus and how the concept has evolved over the years according to new IR technologies. Different approaches to thesaurus construction are introduced, and readings dealing with specific problems and developments in the collection, formation and organisation of thesaurus concepts and terms are presented. Primarily manual construction methods are discussed, but the bibliography also refers to research about techniques for automatic thesaurus construction.

Date

18. 5.2006 20:06:22

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Abstract

This article provides a review of cataloging and classification publications that appeared in the last two years. The review considers the papers in two categories. Cataloging Theories and Practices covers descriptive cataloging, authority control, classification, subject cataloging, cataloging nonbook materials, electronic resources and metadata, and international cooperation. The second section covers other issues related to cataloging, including management, and education and training. Throughout the review, the author identifies trends and important developments in the area of cataloging and classification.

Date

10. 9.2000 17:38:22

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Abstract

This review of 2004 and 2005 serials literature covers the themes of cost, management, and access. Interwoven through the serials literature of these two years are the importance of collaboration, communication, and linkages between scholars, publishers, subscription agents and other intermediaries, and librarians. The emphasis in the literature is on electronic serials and their impact on publishing, libraries, and vendors. In response to the crisis of escalating journal prices and libraries' dissatisfaction with the Big Deal licensing agreements, Open Access journals and publishing models were promoted. Libraries subscribed to or licensed increasing numbers of electronic serials. As a result, libraries sought ways to better manage licensing and subscription data (not handled by traditional integrated library systems) by implementing electronic resources management systems. In order to provide users with better, faster, and more current information on and access to electronic serials, libraries implemented tools and services to provide A-Z title lists, title by title coverage data, MARC records, and OpenURL link resolvers.

Date

10. 9.2000 17:38:22

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Abstract

The literature of the evaluation of Internet search engines is reviewed. Although there have been many studies, there has been little consistency in the way such studies have been carried out. This problem is exacerbated by the fact that recall is virtually impossible to calculate in the fast changing Internet environment, and therefore the traditional Cranfield type of evaluation is not usually possible. A variety of alternative evaluation methods has been suggested to overcome this difficulty. The authors recommend that a standardised set of tools is developed for the evaluation of web search engines so that, in future, comparisons can be made between search engines more effectively, and that variations in performance of any given search engine over time can be tracked. The paper itself does not provide such a standard set of tools, but it investigates the issues and makes preliminary recommendations of the types of tools needed

Source

Journal of documentation. 56(2000) no.2, S.190-211

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Abstract

The topic of electronic journals (e-journals) dominated the serials literature from 2000 to 2003. This review is limited to the events and issues within the broad topics of cost, management, and archiving. Coverage of cost includes such initiatives as PEAK, JACC, BioMed Central, SPARC, open access, the "Big Deal," and "going e-only." Librarians combated the continued price increase trend for journals, fueled in part by publisher mergers, with the economies found with bundled packages and consortial subscriptions. Serials management topics include usage statistics; core title lists; staffing needs; the "A-Z list" and other services from such companies as Serials Solutions; "deep linking"; link resolvers such as SFX; development of standards or guidelines, such as COUNTER and ERMI; tracking of license terms; vendor mergers; and the demise of integrated library systems and a subscription agent's bankruptcy. Librarians archived print volumes in storage facilities due to space shortages. Librarians and publishers struggled with electronic archiving concepts, discussing questions of who, where, and how. Projects such as LOCKSS tested potential solutions, but missing online content due to the Tasini court case and retractions posed more archiving difficulties. The serials literature captured much of the upheaval resulting from the rapid pace of changes, many linked to the advent of e-journals.

Date

10. 9.2000 17:38:22

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Abstract

"Theory weary, theory leery, why can't I be theory cheery?" (Erickson, 2002, p. 269). The field of human-computer interaction (HCI) is rapidly expanding. Alongside the extensive technological developments that are taking place, a profusion of new theories, methods, and concerns has been imported into the field from a range of disciplines and contexts. An extensive critique of recent theoretical developments is presented here together with an overview of HCI practice. A consequence of bringing new theories into the field has been much insightful explication of HCI phenomena and also a broadening of the field's discourse. However, these theoretically based approaches have had limited impact an the practice of interaction design. This chapter discusses why this is so and suggests that different kinds of mechanisms are needed that will enable both designers and researchers to better articulate and theoretically ground the challenges facing them today. Human-computer interaction is bursting at the seams. Its mission, goals, and methods, well established in the '80s, have all greatly expanded to the point that "HCI is now effectively a boundless domain" (Barnard, May, Duke, & Duce, 2000, p. 221). Everything is in a state of flux: The theory driving research is changing, a flurry of new concepts is emerging, the domains and type of users being studied are diversifying, many of the ways of doing design are new, and much of what is being designed is significantly different. Although potentially much is to be gained from such rapid growth, the downside is an increasing lack of direction, structure, and coherence in the field. What was originally a bounded problem space with a clear focus and a small set of methods for designing computer systems that were easier and more efficient to use by a single user is now turning into a diffuse problem space with less clarity in terms of its objects of study, design foci, and investigative methods. Instead, aspirations of overcoming the Digital Divide, by providing universal accessibility, have become major concerns (e.g., Shneiderman, 2002a). The move toward greater openness in the field means that many more topics, areas, and approaches are now considered acceptable in the worlds of research and practice.
A problem with allowing a field to expand eclectically is that it can easily lose coherence. No one really knows what its purpose is anymore or what criteria to use in assessing its contribution and value to both knowledge and practice. For example, among the many new approaches, ideas, methods, and goals now being proposed, how do we know which are acceptable, reliable, useful, and generalizable? Moreover, how do researchers and designers know which of the many tools and techniques to use when doing design and research? To be able to address these concerns, a young field in a state of flux (as is HCI) needs to take stock and begin to reflect an the changes that are happening. The purpose of this chapter is to assess and reflect an the role of theory in contemporary HCI and the extent to which it is used in design practice. Over the last ten years, a range of new theories has been imported into the field. A key question is whether such attempts have been productive in terms of "knowledge transfer." Here knowledge transfer means the translation of research findings (e.g., theory, empirical results, descriptive accounts, cognitive models) from one discipline (e.g., cognitive psychology, sociology) into another (e.g., human-computer interaction, computer supported cooperative work).

Source

Annual review of information science and technology. 38(2004), S.87-144

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Abstract

Does information science have a theory of information? There seems to be a tendency within information science to seek a theory of information, but the search is apparently unproductive (Hjoerland, 1998; Saracevic, 1999). This review brings together work from inside and outside the field of information science, showing that other perspectives an information theory could be of assistance. Constructivist claims that emphasize the uniqueness of the individual experience of information, maintaining that there is no information independent of our social practices (Cornelius, 1996a), are also mentioned. Such a position would be echoed in a symbolic interactionist approach. Conventionally, the history of attempts to develop a theory of information date from the publication of Claude Shannon's work in 1948, and his joint publication of that work with an essay by Warren Weaver in 1949 (Shannon & Weaver, 1949/1963). Information science found itself alongside many other disciplines attempting to develop a theory of information (Machlup & Mansfield, 1983). From Weaver's essay stems the claim that the basic concepts of Shannon's mathematical theory of communication, which Shannon later referred to as a theory of information, can be applied in disciplines outside electrical engineering, even in the social sciences.
Shannon provides a model whereby an information source selects a desired message, out of a set of possible messages, that is then formed into a signal. The signal is sent over the communication channel to a receiver, which then transforms the signal back to a message that is relayed to its destination (Shannon & Weaver, 1949/1963, p. 7). Problems connected with this model have remained with us. Some of the concepts are ambiguous; the identification of information with a process has spancelled the debate; the problems of measuring the amount of information, the relation of information to meaning, and questions about the truth value of information have remained. Balancing attention between the process and the act of receiving information, and deterrnining the character of the receiver, has also been the focus of work and debate. Information science has mined work from other disciplines involving information theory and has also produced its own theory. The desire for theory remains (Hjorland, 1998; Saracevic, 1999), but what theory will deliver is unclear. The distinction between data and information, or communication and information, is not of concern here. The convention that data, at some point of use, become information, and that information is transferred in a process of communication suffices for this discussion. Substitution of any of these terms is not a problem. More problematic is the relationship between information and knowledge. It seems accepted that at some point the data by perception, or selection, become information, which feeds and alters knowledge structures in a human recipient. What that process of alteration is, and its implications, remain problematic. This review considers the following questions: 1. What can be gleaned from the history of reviews of information in information science? 2. What current maps, guides, and surveys are available to elaborate our understanding of the issues? 3. Is there a parallel development of work outside information science an information theory of use to us? 4. Is there a dominant view of information within information science? 5. What can we say about issues like measurement, meaning, and misinformation? 6. Is there other current work of relevance that can assist attempts, in information science, to develop a theory of information?

Source

Annual review of information science and technology. 36(2002), S.393-426

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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."

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Abstract

This chapter reviews research and applications in statistical language modeling for information retrieval (IR), which has emerged within the past several years as a new probabilistic framework for describing information retrieval processes. Generally speaking, statistical language modeling, or more simply language modeling (LM), involves estimating a probability distribution that captures statistical regularities of natural language use. Applied to information retrieval, language modeling refers to the problem of estimating the likelihood that a query and a document could have been generated by the same language model, given the language model of the document either with or without a language model of the query. The roots of statistical language modeling date to the beginning of the twentieth century when Markov tried to model letter sequences in works of Russian literature (Manning & Schütze, 1999). Zipf (1929, 1932, 1949, 1965) studied the statistical properties of text and discovered that the frequency of works decays as a Power function of each works rank. However, it was Shannon's (1951) work that inspired later research in this area. In 1951, eager to explore the applications of his newly founded information theory to human language, Shannon used a prediction game involving n-grams to investigate the information content of English text. He evaluated n-gram models' performance by comparing their crossentropy an texts with the true entropy estimated using predictions made by human subjects. For many years, statistical language models have been used primarily for automatic speech recognition. Since 1980, when the first significant language model was proposed (Rosenfeld, 2000), statistical language modeling has become a fundamental component of speech recognition, machine translation, and spelling correction.

Source

Annual review of information science and technology. 39(2005), S.3-32

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Abstract

Advanced technology has resulted in the generation of about one million terabytes of information every year. Ninety-reine percent of this is available in digital format (Keim, 2001). More information will be generated in the next three years than was created during all of previous human history (Keim, 2001). Collecting information is no longer a problem, but extracting value from information collections has become progressively more difficult. Various search engines have been developed to make it easier to locate information of interest, but these work well only for a person who has a specific goal and who understands what and how information is stored. This usually is not the Gase. Visualization was commonly thought of in terms of representing human mental processes (MacEachren, 1991; Miller, 1984). The concept is now associated with the amplification of these mental processes (Card, Mackinlay, & Shneiderman, 1999). Human eyes can process visual cues rapidly, whereas advanced information analysis techniques transform the computer into a powerful means of managing digitized information. Visualization offers a link between these two potent systems, the human eye and the computer (Gershon, Eick, & Card, 1998), helping to identify patterns and to extract insights from large amounts of information. The identification of patterns is important because it may lead to a scientific discovery, an interpretation of clues to solve a crime, the prediction of catastrophic weather, a successful financial investment, or a better understanding of human behavior in a computermediated environment. Visualization technology shows considerable promise for increasing the value of large-scale collections of information, as evidenced by several commercial applications of TreeMap (e.g., http://www.smartmoney.com) and Hyperbolic tree (e.g., http://www.inxight.com) to visualize large-scale hierarchical structures. Although the proliferation of visualization technologies dates from the 1990s where sophisticated hardware and software made increasingly faster generation of graphical objects possible, the role of visual aids in facilitating the construction of mental images has a long history. Visualization has been used to communicate ideas, to monitor trends implicit in data, and to explore large volumes of data for hypothesis generation. Imagine traveling to a strange place without a map, having to memorize physical and chemical properties of an element without Mendeleyev's periodic table, trying to understand the stock market without statistical diagrams, or browsing a collection of documents without interactive visual aids. A collection of information can lose its value simply because of the effort required for exhaustive exploration. Such frustrations can be overcome by visualization.
Visualization can be classified as scientific visualization, software visualization, or information visualization. Although the data differ, the underlying techniques have much in common. They use the same elements (visual cues) and follow the same rules of combining visual cues to deliver patterns. They all involve understanding human perception (Encarnacao, Foley, Bryson, & Feiner, 1994) and require domain knowledge (Tufte, 1990). Because most decisions are based an unstructured information, such as text documents, Web pages, or e-mail messages, this chapter focuses an the visualization of unstructured textual documents. The chapter reviews information visualization techniques developed over the last decade and examines how they have been applied in different domains. The first section provides the background by describing visualization history and giving overviews of scientific, software, and information visualization as well as the perceptual aspects of visualization. The next section assesses important visualization techniques that convert abstract information into visual objects and facilitate navigation through displays an a computer screen. It also explores information analysis algorithms that can be applied to identify or extract salient visualizable structures from collections of information. Information visualization systems that integrate different types of technologies to address problems in different domains are then surveyed; and we move an to a survey and critique of visualization system evaluation studies. The chapter concludes with a summary and identification of future research directions.

Source

Annual review of information science and technology. 39(2005), S.139-177