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Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Abstract

Online health platforms play an important role in chronic disease management. Patients participate in online health platforms to receive and provide health-related support from each other. However, there remains a debate about whether the influence of social interaction on patient health anxiety is linearly positive. Based on uncertainty, information overload, and the theory of motivational information management, we develop and test a model considering a potential curvilinear relationship between social interaction and health anxiety, as well as a moderating effect of health literacy. We collect patient interaction data from an online health platform based on chronic disease management in China and use text mining and econometrics to test our hypotheses. Specifically, we find an inverted U-shaped relationship between informational provision and health anxiety. Our results also show that information receipt and emotion provision have U-shaped relationships with health anxiety. Interestingly, health literacy can effectively alleviate the U-shaped relationship between information receipt and health anxiety. These findings not only provide new insights into the literature on online patient interactions but also provide decision support for patients and platform managers.

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Source

Classification research for knowledge representation and organization. Proc. 5th Int. Study Conf. on Classification Research, Toronto, Canada, 24.-28.6.1991. Ed. by N.J. Williamson u. M. Hudon

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Abstract

Much literature has been written speculating upon how classification can be used in online catalogs to improve information retrieval. While some empirical studies have been done exploring whether the direct use of traditional classification schemes designed for a manual environment is effective and efficient in the online environment, none has manipulated these manual classifications in such a w ay as to take full advantage of the power of both the classification and computer. It has been suggested by some authors, such as Wajenberg and Drabenstott, that this power could be realized if the individual components of synthesized DDC numbers could be identified and indexed. This paper looks at the feasibility of automatically decomposing DDC synthesized numbers and the implications of such decomposition for information retrieval. Based on an analysis of the instructions for synthesizing numbers in the main class Arts (700) and all DDC Tables, 17 decomposition rules were defined, 13 covering the Add Notes and four the Standard Subdivisions. 1,701 DDC synthesized numbers were decomposed by a computer system called DND (Dewey Number Decomposer), developed by the author. From the 1,701 numbers, 600 were randomly selected fo r examination by three judges, each evaluating 200 numbers. The decomposition success rate was 100% and it was concluded that synthesized DDC numbers can be accurately decomposed automatically. The study has implications for information retrieval, expert systems for assigning DDC numbers, automatic indexing, switching language development, enhancing classifiers' work, teaching library school students, and providing quality control for DDC number assignments. These implications were explored using a prototype retrieval system.

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Date

22. 3.2013 19:50:00