Search (132 results, page 7 of 7)

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  1. Wilkinson, C.L.: Intellectual level as a search enhancement in the online environment : summation and implications (1990) 0.00
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    Abstract
    This paper summarizes the papers presented by the members of the panel on "The Concept of Intellectual Level in Cataloging and Classification." The implication of adding intellectual level to the MARC record and creating intellectual level indexes in online catalogs are discussed. Conclusion is reached that providing intellectual level will not only be costly but may perhaps even be a disservice to library users.
  2. 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) 0.00
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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.
  3. Saif, H.; He, Y.; Fernandez, M.; Alani, H.: Contextual semantics for sentiment analysis of Twitter (2016) 0.00
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    Abstract
    Sentiment analysis on Twitter has attracted much attention recently due to its wide applications in both, commercial and public sectors. In this paper we present SentiCircles, a lexicon-based approach for sentiment analysis on Twitter. Different from typical lexicon-based approaches, which offer a fixed and static prior sentiment polarities of words regardless of their context, SentiCircles takes into account the co-occurrence patterns of words in different contexts in tweets to capture their semantics and update their pre-assigned strength and polarity in sentiment lexicons accordingly. Our approach allows for the detection of sentiment at both entity-level and tweet-level. We evaluate our proposed approach on three Twitter datasets using three different sentiment lexicons to derive word prior sentiments. Results show that our approach significantly outperforms the baselines in accuracy and F-measure for entity-level subjectivity (neutral vs. polar) and polarity (positive vs. negative) detections. For tweet-level sentiment detection, our approach performs better than the state-of-the-art SentiStrength by 4-5% in accuracy in two datasets, but falls marginally behind by 1% in F-measure in the third dataset.
  4. Martindale, C.; McKenzie, D.: On the utility of content analysis in author attribution : 'The federalist' (1995) 0.00
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  5. Hildebrandt, B.; Moratz, R.; Rickheit, G.; Sagerer, G.: Kognitive Modellierung von Sprach- und Bildverstehen (1996) 0.00
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    Source
    Natural language processing and speech technology: Results of the 3rd KONVENS Conference, Bielefeld, October 1996. Ed.: D. Gibbon
  6. Kessel, K.: Who's afraid of the big, bad uktena mster? : subject cataloging for images (2016) 0.00
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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.
  7. From information to knowledge : conceptual and content analysis by computer (1995) 0.00
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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
  8. Konkova, E.; MacFarlane, A.; Göker, A.: Analysing creative image search information needs (2016) 0.00
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    Abstract
    Creative professionals in advertising, marketing, design and journalism search for images to visually represent a concept for their project. The main purpose of this paper is to present search facets derived from an analysis of documents known as briefs, which are widely used in creative industries as requirement documents describing information needs. The briefs specify the type of image required, such as the content and context of use for the image and represent the topic from which the searcher builds an image query. We take three main sources-user image search behaviour, briefs, and image search engine search facets-to examine the search facets for image searching in order to examine the following research question-are search facet schemes for image search engines sufficient for user needs, or is revision needed? We found that there are three main classes of user search facet, which include business, contextual and image related information. The key argument in the paper is that the facet "keyword/tag" is ambiguous and does not support user needs for more generic descriptions to broaden search or specific descriptions to narrow their search-we suggest that a more detailed search facet scheme would be appropriate.
  9. Vieira, L.: Modèle d'analyse pur une classification du document iconographique (1999) 0.00
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    Footnote
    Übers. d. Titels: Analyse model for a classification of iconographic documents
  10. Rowe, N.C.: Inferring depictions in natural-language captions for efficient access to picture data (1994) 0.00
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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
  11. Andersson, R.; Holst, E.: Indexes and other depictions of fictions : a new model for analysis empirically tested (1996) 0.00
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    Abstract
    In this study descriptions of a novel by 100 users at 2 Swedish public libraries, Malmö and Molndal, Mar-Apr 95, were compared to the index terms used for the novels at these libraries. Describes previous systems for fiction indexing, the 2 libraries, and the users interviewed. Compares the AMP system with their own model. The latter operates with terms under the headings phenomena, frame and author's intention. The similarities between the users' and indexers' descriptions were sufficiently close to make it possible to retrieve fiction in accordance with users' wishes in Molndal, and would have been in Malmö, had more books been indexed with more terms. Sometimes the similarities were close enough for users to retrieve fiction on their own
  12. Lassak, L.: ¬Ein Versuch zur Repräsentation von Charakteren der Kinder- und Jugendbuchserie "Die drei ???" in einer Datenbank (2017) 0.00
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    Footnote
    Masterarbeit zur Erlangung des akademischen Grades Master of Arts (M. A.)

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