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Todd, R.J.: Subject access: what's it all about? : some research findings (1993)
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Svenonius, E.: Access to nonbook materials : the limits of subject indexing for visual and aural languages (1994)
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Andersen, J.: ¬The concept of genre : when, how, and why? (2001)
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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)
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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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Pozzi de Sousa, B.; Ortega, C.D.: Aspects regarding the notion of subject in the context of different theoretical trends : teaching approaches in Brazil (2018)
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Hjoerland, B.: Subject (of documents) (2016)
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- Abstract
- This article presents and discusses the concept "subject" or subject matter (of documents) as it has been examined in library and information science (LIS) for more than 100 years. Different theoretical positions are outlined and it is found that the most important distinction is between document-oriented views versus request-oriented views. The document-oriented view conceive subject as something inherent in documents, whereas the request-oriented view (or the policy based view) understand subject as an attribution made to documents in order to facilitate certain uses of them. Related concepts such as concepts, aboutness, topic, isness and ofness are also briefly presented. The conclusion is that the most fruitful way of defining "subject" (of a document) is the documents informative or epistemological potentials, that is, the documents potentials of informing users and advance the development of knowledge.
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Jörgensen, C.: ¬The applicability of selected classification systems to image attributes (1996)
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Hutchins, W.J.: ¬The concept of 'aboutness' in subject indexing (1978)
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Beghtol, C.: Stories : applications of narrative discourse analysis to issues in information storage and retrieval (1997)
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Caldera-Serrano, J.: Thematic description of audio-visual information on television (2010)
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Bi, Y.: Sentiment classification in social media data by combining triplet belief functions (2022)
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