Search (11 results, page 1 of 1)

  • × author_ss:"Chen, J."
  1. Zheng, X.; Chen, J.; Yan, E.; Ni, C.: Gender and country biases in Wikipedia citations to scholarly publications (2023) 0.02 
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    Date
    22. 1.2023 18:53:32
    Source
    Journal of the Association for Information Science and Technology. 74(2023) no.2, S.219-233
  2. Qin, C.; Liu, Y.; Mou, J.; Chen, J.: User adoption of a hybrid social tagging approach in an online knowledge community (2019) 0.01 
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    Abstract
    Purpose Online knowledge communities make great contributions to global knowledge sharing and innovation. Resource tagging approaches have been widely adopted in such communities to describe, annotate and organize knowledge resources mainly through users' participation. However, it is unclear what causes the adoption of a particular resource tagging approach. The purpose of this paper is to identify factors that drive users to use a hybrid social tagging approach. Design/methodology/approach Technology acceptance model and social cognitive theory are adopted to support an integrated model proposed in this paper. Zhihu, one of the most popular online knowledge communities in China, is taken as the survey context. A survey was conducted with a questionnaire and collected data were analyzed through structural equation model. Findings A new hybrid social resource tagging approach was refined and described. The empirical results revealed that self-efficacy, perceived usefulness (PU) and perceived ease of use exert positive effect on users' attitude. Moreover, social influence, PU and attitude impact significantly on users' intention to use a hybrid social resource tagging approach. Originality/value Theoretically, this study enriches the type of resource tagging approaches and recognizes factors influencing user adoption to use it. Regarding the practical parts, the results provide online information system providers and designers with referential strategies to improve the performance of the current tagging approaches and promote them.
    Date
    20. 1.2015 18:30:22
    Source
    Aslib journal of information management. 71(2019) no.2, S.155-175
  3. Qin, J.; Chen, J.: ¬A multi-layered, multi-dimensional representation of digital educational resources (2003) 0.00 
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    Abstract
    Semantic mapping between controlled vocabulary and keywords is the first step towards knowledge-based subject access. This study reports the preliminary result of a semantic mapping experiment for the Gateway to Educational Materials (GEM). A total of 3,555 keywords were mapped with 322 concept names in the GEM controlled vocabulary. The preliminary test to 10,000 metadata records presented widely varied sets of results between the mapped and non-mapped data. The paper discussed linguistic and technical problems encountered in the mapping process and raised issues in the representation technologies and methods, which will lead to future study of knowledge-based access to networked information resources.
    Source
    Subject retrieval in a networked environment: Proceedings of the IFLA Satellite Meeting held in Dublin, OH, 14-16 August 2001 and sponsored by the IFLA Classification and Indexing Section, the IFLA Information Technology Section and OCLC. Ed.: I.C. McIlwaine
    Theme
    Information Gateway
  4. Chen, J.: Artificial intelligence (2009) 0.00 
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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.
    Source
    Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates
  5. Chen, J.: ¬A lexical knowledge base approach for English-Chinese cross-language information retrieval (2006) 0.00 
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    Abstract
    This study proposes and explores a natural language processing- (NLP) based strategy to address out-ofdictionary and vocabulary mismatch problems in query translation based English-Chinese Cross-Language Information Retrieval (EC-CLIR). The strategy, named the LKB approach, is to construct a lexical knowledge base (LKB) and to use it for query translation. In this article, the author describes the LKB construction process, which customizes available translation resources based an the document collection of the EC-CLIR system. The evaluation shows that the LKB approach is very promising. It consistently increased the percentage of correct translations and decreased the percentage of missing translations in addition to effectively detecting the vocabulary gap between the document collection and the translation resource of the system. The comparative analysis of the top EC-CLIR results using the LKB and two other translation resources demonstrates that the LKB approach has produced significant improvement in EC-CLIR performance compared to performance using the original translation resource without customization. It has also achieved the same level of performance as a sophisticated machine translation system. The study concludes that the LKB approach has the potential to be an empirical model for developing real-world CLIR systems. Linguistic knowledge and NLP techniques, if appropriately used, can improve the effectiveness of English-Chinese crosslanguage information retrieval.
    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.2, S.233-243
  6. 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.
    Source
    Journal of the Association for Information Science and Technology. 69(2018) no.1, S.47-59
  7. Hu, X.; Rousseau, R.; Chen, J.: ¬A new approach for measuring the value of patents based on structural indicators for ego patent citation networks (2012) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 63(2012) no.9, S.1834-1842
  8. 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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    Source
    Journal of the Association for Information Science and Technology. 70(2019) no.4, S.385-401
  9. Jiang, X.; Zhu, X.; Chen, J.: Main path analysis on cyclic citation networks (2020) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 71(2020) no.5, S.578-595
  10. Qin, C.; Liu, Y.; Ma, X.; Chen, J.; Liang, H.: Designing for serendipity in online knowledge communities : an investigation of tag presentation formats and openness to experience (2022) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 73(2022) no.10, S.1401-1417
  11. Chen, J.; Wang, D.; Xie, I.; Lu, Q.: Image annotation tactics : transitions, strategies and efficiency (2018) 0.00 
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    Source
    Information processing and management. 54(2018) no.6, S.985-1001

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