Search (10 results, page 1 of 1)

  • × theme_ss:"Inhaltsanalyse"
  1. 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.
  2. 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) 0.02
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    Date
    5. 8.2006 13:22:44
  3. Beghtol, C.: Toward a theory of fiction analysis for information storage and retrieval (1992) 0.01
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    Date
    5. 8.2006 13:22:08
  4. 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) 0.01
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    Date
    22. 5.2021 12:43:05
  5. Raieli, R.: ¬The semantic hole : enthusiasm and caution around multimedia information retrieval (2012) 0.01
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    Date
    22. 1.2012 13:02:10
    Source
    Knowledge organization. 39(2012) no.1, S.13-22
  6. Weimer, K.H.: ¬The nexus of subject analysis and bibliographic description : the case of multipart videos (1996) 0.01
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    Source
    Cataloging and classification quarterly. 22(1996) no.2, S.5-18
  7. Chen, S.-J.; Lee, H.-L.: Art images and mental associations : a preliminary exploration (2014) 0.01
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    Source
    Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
  8. White, M.D.; Marsh, E.E.: Content analysis : a flexible methodology (2006) 0.01
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    Source
    Library trends. 55(2006) no.1, S.22-45
  9. 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
  10. Bade, D.: ¬The creation and persistence of misinformation in shared library catalogs : language and subject knowledge in a technological era (2002) 0.00
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    Date
    22. 9.1997 19:16:05