Search (24 results, page 1 of 2)

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Abstract

Presents an overview of some recent developments in the clause-based content analysis of linguistic data. Introduces network analysis of evaluative texts, for the analysis of cognitive maps, and linguistic content analysis. Focuses on the types of substantive inferences afforded by the three approaches

Source

Social science computer review. 11(1993) no.3, S.283-291

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Content

This paper examines three themes in the design of search support services: linking different genres of reference resources (e.g. bibliographies, biographical dictionaries, catalogs, encyclopedias, place name gazetteers); the division of vocabularies by facet (e.g. What, Where, When, and Who); and mapping between both similar and dissimilar vocabularies. Different vocabularies within a facet can be used in conjunction, e.g. a place name combined with spatial coordinates for Where. In practice, vocabularies of different facets are used in combination in the representation or description of complex topics. Rich opportunities arise from mapping across vocabularies of dissimilar reference genres to recreate the amenities of a reference library. In a network environment, in which vocabulary control cannot be imposed, semantic correspondence across diverse vocabularies is a challenge and an opportunity.

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Source

Encyclopedia of computer science and technology, vol.6

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Abstract

Presents a framework for knowledge discovery and concept exploration. In order to enhance the concept exploration capability of knowledge based systems and to alleviate the limitation of the manual browsing approach, develops 2 spreading activation based algorithms for concept exploration in large, heterogeneous networks of concepts (eg multiple thesauri). One algorithm, which is based on the symbolic AI paradigma, performs a conventional branch-and-bound search on a semantic net representation to identify other highly relevant concepts (a serial, optimal search process). The 2nd algorithm, which is absed on the neural network approach, executes the Hopfield net parallel relaxation and convergence process to identify 'convergent' concepts for some initial queries (a parallel, heuristic search process). Tests these 2 algorithms on a large text-based knowledge network of about 13.000 nodes (terms) and 80.000 directed links in the area of computing technologies

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Source

Text analysis and computer. Ed.: C. Züll et al

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Content

SCHMIDT, K.M.: Concepts - content - meaning: an introduction; DUCHASTEL, J. et al.: The SACAO project: using computation toward textual data analysis; PAQUIN, L.-C. u. L. DUPUY: An approach to expertise transfer: computer-assisted text analysis; HOGENRAAD, R., Y. BESTGEN u. J.-L. NYSTEN: Terrorist rhetoric: texture and architecture; MOHLER, P.P.: On the interaction between reading and computing: an interpretative approach to content analysis; LANCASHIRE, I.: Computer tools for cognitive stylistics; MERGENTHALER, E.: An outline of knowledge based text analysis; NAMENWIRTH, J.Z.: Ideography in computer-aided content analysis; WEBER, R.P. u. J.Z. Namenwirth: Content-analytic indicators: a self-critique; McKINNON, A.: Optimizing the aberrant frequency word technique; ROSATI, R.: Factor analysis in classical archaeology: export patterns of Attic pottery trade; PETRILLO, P.S.: Old and new worlds: ancient coinage and modern technology; DARANYI, S., S. MARJAI u.a.: Caryatids and the measurement of semiosis in architecture; ZARRI, G.P.: Intelligent information retrieval: an application in the field of historical biographical data; BOUCHARD, G., R. ROY u.a.: Computers and genealogy: from family reconstitution to population reconstruction; DEMÉLAS-BOHY, M.-D. u. M. RENAUD: Instability, networks and political parties: a political history expert system prototype; DARANYI, S., A. ABRANYI u. G. KOVACS: Knowledge extraction from ethnopoetic texts by multivariate statistical methods; FRAUTSCHI, R.L.: Measures of narrative voice in French prose fiction applied to textual samples from the enlightenment to the twentieth century; DANNENBERG, R. u.a.: A project in computer music: the musician's workbench

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Abstract

Issues concerning the formulation and application of a model of how humans value information are examined. Formulation of a value function is based on research from modelling, value assessment, human information seeking behavior, and human decision making. The proposed function is incorporated into a computer-based fiction retrieval system and evaluated using data from nine searches. Evaluation is based on the ability of an individual's value function to discriminate among novels selected, rejected, and not considered. The results are discussed in terms of both formulation and utilization of a value function as well as the implications for extending the proposed formulation to other information seeking environments

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Abstract

Purpose - The purpose of this paper is to examine the art historical antecedents of providing subject access to images. After reviewing the assumptions and limitations inherent in the most prevalent descriptive method, the paper seeks to introduce a new model that allows for more comprehensive representation of visually-based cultural materials. Design/methodology/approach - The paper presents a literature-based conceptual analysis, taking Panofsky's theory of iconography and iconology as the starting-point. Panofsky's conceptual model, while appropriate for art created in the Western academic tradition, ignores or misrepresents work from other eras or cultures. Continued dependence on Panofskian descriptive methods limits the functionality and usefulness of image representation systems. Findings - The paper recommends the development of a more precise and inclusive descriptive model for art objects, which is based on the premise that art is not another sort of text, and should not be interpreted as such. Practical implications - The paper provides suggestions for the development of representation models that will enhance the description of non-textual artifacts. Originality/value - The paper addresses issues in information science, the history of art, and computer science, and suggests that a new descriptive model would be of great value to both humanist and social science scholars.

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Date

5. 8.2006 13:22:44

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Abstract

The fan of past documents may be seen across time as a philosophical "wake," translated documents as a sideways relationship and future documents as another fan spreading forward from a given document (p. 365). The "overlap of reading histories can be used to detect common interests among readers," (p. 365) and readers may be classified accordingly. Finally, Fairthorne rejects the notion of a "general" classification, which he regards as a mirage, to be replaced by a citation-type network to identify classes. An interesting feature of his work lies in his linkage between old and new documents via a bibliographic method-citations, authors' names, imprints, style, and vocabulary - rather than topical (subject) terms. This is an indirect method of creating classes. The subject (aboutness) is conceived as a finite, common sharing of knowledge over time (past, present, and future) as opposed to the more common hierarchy of topics in an infinite schema assumed to be universally useful. Fairthorne, a mathematician by training, is a prolific writer an the foundations of classification and information. His professional career includes work with the Royal Engineers Chemical Warfare Section and the Royal Aircraft Establishment (RAE). He was the founder of the Computing Unit which became the RAE Mathematics Department.

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Date

22. 9.1997 19:16:05

Footnote

Rez. in JASIST 54(2003) no.4, S.356-357 (S.J. Lincicum): "Reliance upon shared cataloging in academic libraries in the United States has been driven largely by the need to reduce the expense of cataloging operations without muck regard for the Impact that this approach might have an the quality of the records included in local catalogs. In recent years, ever increasing pressures have prompted libraries to adopt practices such as "rapid" copy cataloging that purposely reduce the scrutiny applied to bibliographic records downloaded from shared databases, possibly increasing the number of errors that slip through unnoticed. Errors in bibliographic records can lead to serious problems for library catalog users. If the data contained in bibliographic records is inaccurate, users will have difficulty discovering and recognizing resources in a library's collection that are relevant to their needs. Thus, it has become increasingly important to understand the extent and nature of errors that occur in the records found in large shared bibliographic databases, such as OCLC WorldCat, to develop cataloging practices optimized for the shared cataloging environment. Although this monograph raises a few legitimate concerns about recent trends in cataloging practice, it fails to provide the "detailed look" at misinformation in library catalogs arising from linguistic errors and mistakes in subject analysis promised by the publisher. A basic premise advanced throughout the text is that a certain amount of linguistic and subject knowledge is required to catalog library materials effectively. The author emphasizes repeatedly that most catalogers today are asked to catalog an increasingly diverse array of materials, and that they are often required to work in languages or subject areas of which they have little or no knowledge. He argues that the records contributed to shared databases are increasingly being created by catalogers with inadequate linguistic or subject expertise. This adversely affects the quality of individual library catalogs because errors often go uncorrected as records are downloaded from shared databases to local catalogs by copy catalogers who possess even less knowledge. Calling misinformation an "evil phenomenon," Bade states that his main goal is to discuss, "two fundamental types of misinformation found in bibliographic and authority records in library catalogs: that arising from linguistic errors, and that caused by errors in subject analysis, including missing or wrong subject headings" (p. 2). After a superficial discussion of "other" types of errors that can occur in bibliographic records, such as typographical errors and errors in the application of descriptive cataloging rules, Bade begins his discussion of linguistic errors. He asserts that sharing bibliographic records created by catalogers with inadequate linguistic or subject knowledge has, "disastrous effects an the library community" (p. 6). To support this bold assertion, Bade provides as evidence little more than a laundry list of errors that he has personally observed in bibliographic records over the years. When he eventually cites several studies that have addressed the availability and quality of records available for materials in languages other than English, he fails to describe the findings of these studies in any detail, let alone relate the findings to his own observations in a meaningful way. Bade claims that a lack of linguistic expertise among catalogers is the "primary source for linguistic misinformation in our databases" (p. 10), but he neither cites substantive data from existing studies nor provides any new data regarding the overall level of linguistic knowledge among catalogers to support this claim. The section concludes with a brief list of eight sensible, if unoriginal, suggestions for coping with the challenge of cataloging materials in unfamiliar languages.

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Date

5. 8.2006 13:22:08

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Date

22. 5.2021 12:43:05

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Abstract

This guide, for beginning catalogers with humanities or social sciences backgrounds, provides assistance in subject analysis (based on Library of Congress Subject Headings) of theses and dissertations (T/Ds) that are produced by graduate students in university departments in the hard sciences (physical sciences and engineering). It is aimed at those who have had little or no experience in cataloging, especially of this type of material, and for those who desire to supplement local mentoring resources for subject analysis in the hard sciences. Theses and dissertations from these departments present a special challenge because they are the results of current research representing specific new concepts with which the cataloger may not be familiar. In fact, subject headings often have not yet been created for the specific concept(s) being researched. Additionally, T/D authors often use jargon/terminology specific to their department. Catalogers often have many other duties in addition to subject analysis of T/Ds in the hard sciences, yet they desire to provide optimal access through accurate, thorough subject analysis. Tips are provided for determining the content of the T/D, strategic searches on WorldCat for possible subject headings, evaluating the relevancy of these subject headings for final selection, and selecting appropriate subdivisions where needed. Lists of basic reference resources are also provided.

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Abstract

It is vital for library and information science to understand the subject indexing process thoroughly. However, document analysis, the first and most important step in indexing, has not received sufficient attention. As this is an exceptionally hard problem, we still do not dispose of a sound indexing theory. Therefore we have difficulties in teaching indexing and in explaining why a given subject representation is "better" than another. Technological advancements have not helped to close this fundamental gap. To proceed, we should ask the right questions instead. Several types of indexer inconsistencies can be explained as acceptable, yet different conceptualizations which resulting of the variety of groups dealing with a problem from their respective viewpoints. Multiple indexed documents are regarded as the normal case. Intersubjectively replicable indexing results are often questionable or do not constitute interesting cases of indexing at all. In the context of my ongoing dissertation in which I intend to develop an enhanced indexing theory by investigating improvements within a social sciences domain, this paper explains user-oriented selective depth analysis and why I chose that configuration. Strongly influenced by Mai's dissertation, I also communicate my first insights concerning current indexing theories. I agree that I cannot ignore epistemological stances and philosophical issues in language and meaning related to indexing and accept the openness of the interpretive nature of the indexing process. Although I present arguments against the employment of an indexing language as well, it is still indispensable in situations which demand easier access and control by devices. Despite the enormous difficulties the user-oriented and selective depth analysis poses, I argue that it is both feasible and useful if one achieves careful guidance of the possible interpretations. There is some hope because the number of useful interpretations is limited: Every summary is tailored to a purpose, audience and situation. Domain, discourse and social practice entail additional constraints. A pluralistic method mix that focusses on ecologically valid, holistic contexts and employs qualitative methods is recommended. Domain analysis urgently has to be made more practical and applicable. Only then we will be able to investigate empirically domains in order to identify their structures shaped by the corresponding discourse communities. We plan to represent the recognized problem structures and indexing questions of relevance to a small domain in formal, ontological computer models -- if we can find such stable knowledge structures. This would allow us to tailor dynamically summaries for user communities. For practical purposes we suggest to assume a less demanding position than Hjorland's "totality of the epistemological potential". It is sufficent that we identify and represent iteratively the information needs of today's user groups in interactive knowledge-based systems. The best way to formalize such knowledge gained about discourse communities is however unknown. Indexers should stay in direct contact with the community they serve or be part of it to ensure agreement with their viewpoints. Checklist/request-oriented indexing could be very helpful but it remains to be demonstrated how well it will be applicable in the social sciences. A frame-based representation or at least a sophisticated grouping of terms could help to express relational knowledge structures. There remains much work to do since in practice no one has shown yet how such an improved indexing system would work and if the indexing results were really "better".

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Abstract

In recent years, there has been a rapid growth of user-generated data in collaborative tagging (a.k.a. folksonomy-based) systems due to the prevailing of Web 2.0 communities. To effectively assist users to find their desired resources, it is critical to understand user behaviors and preferences. Tag-based profile techniques, which model users and resources by a vector of relevant tags, are widely employed in folksonomy-based systems. This is mainly because that personalized search and recommendations can be facilitated by measuring relevance between user profiles and resource profiles. However, conventional measurements neglect the sentiment aspect of user-generated tags. In fact, tags can be very emotional and subjective, as users usually express their perceptions and feelings about the resources by tags. Therefore, it is necessary to take sentiment relevance into account into measurements. In this paper, we present a novel generic framework SenticRank to incorporate various sentiment information to various sentiment-based information for personalized search by user profiles and resource profiles. In this framework, content-based sentiment ranking and collaborative sentiment ranking methods are proposed to obtain sentiment-based personalized ranking. To the best of our knowledge, this is the first work of integrating sentiment information to address the problem of the personalized tag-based search in collaborative tagging systems. Moreover, we compare the proposed sentiment-based personalized search with baselines in the experiments, the results of which have verified the effectiveness of the proposed framework. In addition, we study the influences by popular sentiment dictionaries, and SenticNet is the most prominent knowledge base to boost the performance of personalized search in folksonomy.

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Date

22. 1.2012 13:02:10

Source

Knowledge organization. 39(2012) no.1, S.13-22

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Source

Cataloging and classification quarterly. 22(1996) no.2, S.5-18