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Chen, J.: Artificial intelligence (2009) 0.01
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Abstract

Artificial intelligence (AI) is a multidisciplinary subject, typically studied as a research area within Computer Science. AI study aims at achieving a good understanding of the nature of intelligence and building intelligent agents which are computational systems demonstrating intelligent behavior. AI has been developed over more than 50 years. The topics studied in AI are quite broad, ranging from knowledge representation and reasoning, knowledge-based systems, machine learning and data mining, natural language processing, to search, image processing, robotics, and intelligent information systems. Numerous successful AI systems have been deployed in real-life applications in engineering, finance, science, health care, education, and service sectors. AI research has also significantly impacted the subject area of Library and Information Science (LIS), helping to develop smart Web search engines, personalized news filters, and knowledge-sharing and indexing systems. This entry briefly outlines the main topics studied in AI, samples some typical successful AI applications, and discusses the cross-fertilization between AI and LIS.
Shen, X.-L.; Li, Y.-J.; Sun, Y.; Chen, J.; Wang, F.: Knowledge withholding in online knowledge spaces : social deviance behavior and secondary control perspective (2019) 0.00
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Abstract

Knowledge withholding, which is defined as the likelihood that an individual devotes less than full effort to knowledge contribution, can be regarded as an emerging social deviance behavior for knowledge practice in online knowledge spaces. However, prior studies placed a great emphasis on proactive knowledge behaviors, such as knowledge sharing and contribution, but failed to consider the uniqueness of knowledge withholding. To capture the social-deviant nature of knowledge withholding and to better understand how people deal with counterproductive knowledge behaviors, this study develops a research model based on the secondary control perspective. Empirical analyses were conducted using the data collected from an online knowledge space. The results indicate that both predictive control and vicarious control exert a positive influence on knowledge withholding. This study also incorporates knowledge-withholding acceptability as a moderating variable of secondary control strategies. In particular, knowledge-withholding acceptability enhances the impact of predictive control, whereas it weakens the effect of vicarious control on knowledge withholding. This study concludes with a discussion of the key findings, and the implications for both research and practice.
Reyes Ayala, B.; Knudson, R.; Chen, J.; Cao, G.; Wang, X.: Metadata records machine translation combining multi-engine outputs with limited parallel data (2018) 0.00
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Abstract

One way to facilitate Multilingual Information Access (MLIA) for digital libraries is to generate multilingual metadata records by applying Machine Translation (MT) techniques. Current online MT services are available and affordable, but are not always effective for creating multilingual metadata records. In this study, we implemented 3 different MT strategies and evaluated their performance when translating English metadata records to Chinese and Spanish. These strategies included combining MT results from 3 online MT systems (Google, Bing, and Yahoo!) with and without additional linguistic resources, such as manually-generated parallel corpora, and metadata records in the two target languages obtained from international partners. The open-source statistical MT platform Moses was applied to design and implement the three translation strategies. Human evaluation of the MT results using adequacy and fluency demonstrated that two of the strategies produced higher quality translations than individual online MT systems for both languages. Especially, adding small, manually-generated parallel corpora of metadata records significantly improved translation performance. Our study suggested an effective and efficient MT approach for providing multilingual services for digital collections.

Zheng, X.; Chen, J.; Yan, E.; Ni, C.: Gender and country biases in Wikipedia citations to scholarly publications (2023) 0.00

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Date: 22. 1.2023 18:53:32

Qin, C.; Liu, Y.; Mou, J.; Chen, J.: User adoption of a hybrid social tagging approach in an online knowledge community (2019) 0.00

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Date: 20. 1.2015 18:30:22

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