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Tay, W.; Zhang, X.; Karimi , S.: Beyond mean rating : probabilistic aggregation of star ratings based on helpfulness (2020)
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- Abstract
- The star-rating mechanism of customer reviews is used universally by the online population to compare and select merchants, movies, products, and services. The consensus opinion from aggregation of star ratings is used as a proxy for item quality. Online reviews are noisy and effective aggregation of star ratings to accurately reflect the "true quality" of products and services is challenging. The mean-rating aggregation model is widely used and other aggregation models are also proposed. These existing aggregation models rely on a large number of reviews to tolerate noise. However, many products rarely have reviews. We propose probabilistic aggregation models for review ratings based on the Dirichlet distribution to combat data sparsity in reviews. We further propose to exploit the "helpfulness" social information and time to filter noisy reviews and effectively aggregate ratings to compute the consensus opinion. Our experiments on an Amazon data set show that our probabilistic aggregation models based on "helpfulness" achieve better performance than the statistical and heuristic baseline approaches.
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Ho, S.M.; Bieber, M.; Song, M.; Zhang, X.: Seeking beyond with IntegraL : a user study of sense-making enabled by anchor-based virtual integration of library systems (2013)
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- Abstract
- This article presents a user study showing the effectiveness of a linked-based, virtual integration infrastructure that gives users access to relevant online resources, empowering them to design an information-seeking path that is specifically relevant to their context. IntegraL provides a lightweight approach to improve and augment search functionality by dynamically generating context-focused "anchors" for recognized elements of interest generated by library services. This article includes a description of how IntegraL's design supports users' information-seeking behavior. A full user study with both objective and subjective measures of IntegraL and hypothesis testing regarding IntegraL's effectiveness of the user's information-seeking experience are described along with data analysis, implications arising from this kind of virtual integration, and possible future directions.
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Zhang, X.; Wang, D.; Tang, Y.; Xiao, Q.: How question type influences knowledge withholding in social Q&A community (2023)
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- Date
- 22. 9.2023 13:51:47
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Zhang, X.: Concept integration of document databases using different indexing languages (2006)
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- Source
- Information processing and management. 42(2006) no.1, S.121-135
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Yang, F.; Zhang, X.: Focal fields in literature on the information divide : the USA, China, UK and India (2020)
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- Date
- 13. 2.2020 18:22:13
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Zhang, X.; Han, H.: ¬An empirical testing of user stereotypes of information retrieval systems (2005)
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- Source
- Information processing and management. 41(2005) no.3, S.651-664
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Jiang, Y.; Zhang, X.; Tang, Y.; Nie, R.: Feature-based approaches to semantic similarity assessment of concepts using Wikipedia (2015)
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- Source
- Information processing and management. 51(2015) no.3, S.215-234
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Jiang, Y.; Bai, W.; Zhang, X.; Hu, J.: Wikipedia-based information content and semantic similarity computation (2017)
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- Source
- Information processing and management. 53(2017) no.1, S.248-265
