Search (30 results, page 1 of 2)

  • × theme_ss:"Inhaltsanalyse"
  1. Rowe, N.C.: Inferring depictions in natural-language captions for efficient access to picture data (1994) 0.05 
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    Abstract
    Multimedia data can require significant examination time to find desired features ('content analysis'). An alternative is using natural-language captions to describe the data, and matching captions to English queries. But it is hard to include everything in the caption of a complicated datum, so significant content analysis may still seem required. We discuss linguistic clues in captions, both syntactic and semantic, that can simplify or eliminate content analysis. We introduce the notion of content depiction and ruled for depiction inference. Our approach is implemented in an expert system which demonstrated significant increases in recall in experiments
    Source
    Information processing and management. 30(1994) no.3, S.379-388
  2. Beghtol, C.: Toward a theory of fiction analysis for information storage and retrieval (1992) 0.03 
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    Abstract
    This paper examnines various isues that arise in establishing a theoretical basis for an experimental fiction analysis system. It analyzes the warrants of fiction and of works about fiction. From this analysis, it derives classificatory requirements for a fiction system. Classificatory techniques that may contribute to the specification of data elements in fiction are suggested
    Date
    5. 8.2006 13:22:08
  3. Hauff-Hartig, S.: Automatische Transkription von Videos : Fernsehen 3.0: Automatisierte Sentimentanalyse und Zusammenstellung von Kurzvideos mit hohem Aufregungslevel KI-generierte Metadaten: Von der Technologiebeobachtung bis zum produktiven Einsatz (2021) 0.03 
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    Date
    22. 5.2021 12:43:05
    Source
    Open Password. 2021, Nr.947 vom 14.07.2021 [https://www.password-online.de/?mailpoet_router&endpoint=view_in_browser&action=view&data=WzMxOCwiNjczMmIwMzRlMDdmIiwwLDAsMjg4LDFd]
  4. Morehead, D.R.; Pejtersen, A.M.; Rouse, W.B.: ¬The value of information and computer-aided information seeking : problem formulation and application to fiction retrieval (1984) 0.03 
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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
    Source
    Information processing and management. 20(1984), S.583-601
  5. Bertola, F.; Patti, V.: Ontology-based affective models to organize artworks in the social semantic web (2016) 0.03 
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    Abstract
    In this paper, we focus on applying sentiment analysis to resources from online art collections, by exploiting, as information source, tags intended as textual traces that visitors leave to comment artworks on social platforms. We present a framework where methods and tools from a set of disciplines, ranging from Semantic and Social Web to Natural Language Processing, provide us the building blocks for creating a semantic social space to organize artworks according to an ontology of emotions. The ontology is inspired by the Plutchik's circumplex model, a well-founded psychological model of human emotions. Users can be involved in the creation of the emotional space, through a graphical interactive interface. The development of such semantic space enables new ways of accessing and exploring art collections. The affective categorization model and the emotion detection output are encoded into W3C ontology languages. This gives us the twofold advantage to enable tractable reasoning on detected emotions and related artworks, and to foster the interoperability and integration of tools developed in the Semantic Web and Linked Data community. The proposal has been evaluated against a real-word case study, a dataset of tagged multimedia artworks from the ArsMeteo Italian online collection, and validated through a user study.
    Source
    Information processing and management. 52(2016) no.1, S.139-162
  6. Xie, H.; Li, X.; Wang, T.; Lau, R.Y.K.; Wong, T.-L.; Chen, L.; Wang, F.L.; Li, Q.: Incorporating sentiment into tag-based user profiles and resource profiles for personalized search in folksonomy (2016) 0.02 
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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.
    Source
    Information processing and management. 52(2016) no.1, S.61-72
  7. Taylor, S.L.: Integrating natural language understanding with document structure analysis (1994) 0.02 
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    Abstract
    Document understanding, the interpretation of a document from its image form, is a technology area which benefits greatly from the integration of natural language processing with image processing. Develops a prototype of an Intelligent Document Understanding System (IDUS) which employs several technologies: image processing, optical character recognition, document structure analysis and text understanding in a cooperative fashion. Discusses those areas of research during development of IDUS where it is found that the most benefit from the integration of natural language processing and image processing occured: document structure analysis, OCR correction, and text analysis. Discusses 2 applications which are supported by IDUS: text retrieval and automatic generation of hypertext links
  8. Roberts, C.W.; Popping, R.: Computer-supported content analysis : some recent developments (1993) 0.01 
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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
  9. Solomon, P.: Access to fiction for children : a user-based assessment of options and opportunities (1997) 0.01 
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    Abstract
    Reports on a study of children's intentions, purposes, search terms, strategies, successes and breakdowns in accessing fiction. Data was gathered using naturalistic methods of persistent, intensive observation and questioning with children in several school library media centres in the USA, including 997 OPAC transactions. Analyzes the data and highlights aspects of the broader context of the system which may help in development of mechanisms for electronic access
  10. Hildebrandt, B.; Moratz, R.; Rickheit, G.; Sagerer, G.: Kognitive Modellierung von Sprach- und Bildverstehen (1996) 0.01 
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    Source
    Natural language processing and speech technology: Results of the 3rd KONVENS Conference, Bielefeld, October 1996. Ed.: D. Gibbon
  11. Bade, D.: ¬The creation and persistence of misinformation in shared library catalogs : language and subject knowledge in a technological era (2002) 0.01 
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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.
  12. Sauperl, A.: Subject determination during the cataloging process : the development of a system based on theoretical principles (2002) 0.01 
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    Date
    27. 9.2005 14:22:19
    Footnote
    Rez. in: Knowledge organization 30(2003) no.2, S.114-115 (M. Hudon); "This most interesting contribution to the literature of subject cataloguing originates in the author's doctoral dissertation, prepared under the direction of jerry Saye at the University of North Carolina at Chapel Hill. In seven highly readable chapters, Alenka Sauperl develops possible answers to her principal research question: How do cataloguers determine or identify the topic of a document and choose appropriate subject representations? Specific questions at the source of this research an a process which has not been a frequent object of study include: Where do cataloguers look for an overall sense of what a document is about? How do they get an overall sense of what a document is about, especially when they are not familiar with the discipline? Do they consider only one or several possible interpretations? How do they translate meanings in appropriate and valid class numbers and subject headings? Using a strictly qualitative methodology, Dr. Sauperl's research is a study of twelve cataloguers in reallife situation. The author insists an the holistic rather than purely theoretical understanding of the process she is targeting. Participants in the study were professional cataloguers, with at least one year experience in their current job at one of three large academic libraries in the Southeastern United States. All three libraries have a large central cataloguing department, and use OCLC sources and the same automated system; the context of cataloguing tasks is thus considered to be reasonably comparable. All participants were volunteers in this study which combined two datagathering techniques: the think-aloud method and time-line interviews. A model of the subject cataloguing process was first developed from observations of a group of six cataloguers who were asked to independently perform original cataloguing an three nonfiction, non-serial items selected from materials regularly assigned to them for processing. The model was then used for follow-up interviews. Each participant in the second group of cataloguers was invited to reflect an his/her work process for a recent challenging document they had catalogued. Results are presented in 12 stories describing as many personal approaches to subject cataloguing. From these stories a summarization is offered and a theoretical model of subject cataloguing is developed which, according to the author, represents a realistic approach to subject cataloguing. Stories alternate comments from the researcher and direct quotations from the observed or interviewed cataloguers. Not surprisingly, the participants' stories reveal similarities in the sequence and accomplishment of several tasks in the process of subject cataloguing. Sauperl's proposed model, described in Chapter 5, includes as main stages: 1) Examination of the book and subject identification; 2) Search for subject headings; 3) Classification. Chapter 6 is a hypothetical Gase study, using the proposed model to describe the various stages of cataloguing a hypothetical resource. ...
  13. Kessel, K.: Who's afraid of the big, bad uktena mster? : subject cataloging for images (2016) 0.01 
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    Abstract
    This article describes the difference between cataloging images and cataloging books, the obstacles to including subject data in image cataloging records and how these obstacles can be overcome to make image collections more accessible. I call for participants to help create a subject authority reference resource for non-Western art. This article is an expanded and revised version of a presentation for the 2016 Joint ARLIS/VRA conference in Seattle.
  14. From information to knowledge : conceptual and content analysis by computer (1995) 0.01 
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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
  15. Thelwall, M.; Buckley, K.; Paltoglou, G.: Sentiment strength detection for the social web (2012) 0.01 
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    Abstract
    Sentiment analysis is concerned with the automatic extraction of sentiment-related information from text. Although most sentiment analysis addresses commercial tasks, such as extracting opinions from product reviews, there is increasing interest in the affective dimension of the social web, and Twitter in particular. Most sentiment analysis algorithms are not ideally suited to this task because they exploit indirect indicators of sentiment that can reflect genre or topic instead. Hence, such algorithms used to process social web texts can identify spurious sentiment patterns caused by topics rather than affective phenomena. This article assesses an improved version of the algorithm SentiStrength for sentiment strength detection across the social web that primarily uses direct indications of sentiment. The results from six diverse social web data sets (MySpace, Twitter, YouTube, Digg, Runners World, BBC Forums) indicate that SentiStrength 2 is successful in the sense of performing better than a baseline approach for all data sets in both supervised and unsupervised cases. SentiStrength is not always better than machine-learning approaches that exploit indirect indicators of sentiment, however, and is particularly weaker for positive sentiment in news-related discussions. Overall, the results suggest that, even unsupervised, SentiStrength is robust enough to be applied to a wide variety of different social web contexts.
  16. Chen, H.: ¬An analysis of image queries in the field of art history (2001) 0.01 
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    Abstract
    Chen arranged with an Art History instructor to require 20 medieval art images in papers received from 29 students. Participants completed a self administered presearch and postsearch questionnaire, and were interviewed after questionnaire analysis, in order to collect both the keywords and phrases they planned to use, and those actually used. Three MLIS student reviewers then mapped the queries to Enser and McGregor's four categories, Jorgensen's 12 classes, and Fidel's 12 feature data and object poles providing a degree of match on a seven point scale (one not at all to 7 exact). The reviewers give highest scores to Enser and McGregor;'s categories. Modifications to both the Enser and McGregor and Jorgensen schemes are suggested
  17. Short, M.: Text mining and subject analysis for fiction; or, using machine learning and information extraction to assign subject headings to dime novels (2019) 0.01 
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    Theme
    Data Mining
  18. Farrow, J.: All in the mind : concept analysis in indexing (1995) 0.01 
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    Abstract
    The indexing process consists of the comprehension of the document to be indexed, followed by the production of a set of index terms. Differences between academic indexing and back-of-the-book indexing are discussed. Text comprehension is a branch of human information processing, and it is argued that the model of text comprehension and production debeloped by van Dijk and Kintsch can form the basis for a cognitive process model of indexing. Strategies for testing such a model are suggested
  19. Pejtersen, A.M.: Design of a classification scheme for fiction based on an analysis of actual user-librarian communication, and use of the scheme for control of librarians' search strategies (1980) 0.01 
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    Date
    5. 8.2006 13:22:44
  20. Rorissa, A.; Iyer, H.: Theories of cognition and image categorization : what category labels reveal about basic level theory (2008) 0.01 
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    Abstract
    Information search and retrieval interactions usually involve information content in the form of document collections, information retrieval systems and interfaces, and the user. To fully understand information search and retrieval interactions between users' cognitive space and the information space, researchers need to turn to cognitive models and theories. In this article, the authors use one of these theories, the basic level theory. Use of the basic level theory to understand human categorization is both appropriate and essential to user-centered design of taxonomies, ontologies, browsing interfaces, and other indexing tools and systems. Analyses of data from two studies involving free sorting by 105 participants of 100 images were conducted. The types of categories formed and category labels were examined. Results of the analyses indicate that image category labels generally belong to superordinate to the basic level, and are generic and interpretive. Implications for research on theories of cognition and categorization, and design of image indexing, retrieval and browsing systems are discussed.

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