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  • SAGE Publications  (4)
  • General works  (4)
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  • SAGE Publications  (4)
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  • General works  (4)
RVK
  • 1
    Online Resource
    Online Resource
    An Evaluation of the Construction of Information Laws and Regulations in China with Recommendations for Improvement
    SAGE Publications ; 2004
    In:  Journal of Information Science Vol. 30, No. 4 ( 2004-08), p. 321-336
    Details
    In: Journal of Information Science, SAGE Publications, Vol. 30, No. 4 ( 2004-08), p. 321-336
    Abstract: The Chinese Information Law Database was built in the context of an absence of positive analysis in the field of information law. We analyzed the data in this database from several angles. This article systematically shows the fruits of the research and elaborates on the findings deriving from the research. In particular, the achievements and deficiencies in the construction of Chinese information laws and regulations are disclosed. Rapid development, large quantity and legislation diversity characterize the accomplishment, while the poor quality and lack of systematization, stability and continuity represent most of the drawbacks. In the last chapter of this paper, we propose some constructive countermeasures to improve the information legislation, which are also feasible in China. Establishing specific institutions and reinforcing government leadership and control, improving the process of enactment and execution of information laws and regulations, drawing on the legislative experience of developed countries for reference, and strengthening research into information law and regulating information jurisprudence are the most important measures described.
    Type of Medium: Online Resource
    ISSN: 0165-5515 , 1741-6485
    URL: Article
    DOI: 10.1177/0165551504045852
    RVK:
    AN 10100
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2004
    detail.hit.zdb_id: 439125-1
    detail.hit.zdb_id: 2025062-9
    SSG: 24,1
    Location Call Number Limitation Availability
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    Online Resource
  • 2
    Online Resource
    Online Resource
    A hybrid approach for article recommendation in research social networks
    SAGE Publications ; 2018
    In:  Journal of Information Science Vol. 44, No. 5 ( 2018-10), p. 696-711
    Details
    In: Journal of Information Science, SAGE Publications, Vol. 44, No. 5 ( 2018-10), p. 696-711
    Abstract: With the prevalence of research social networks, determining effective methods for recommending scientific articles to online scholars has become a challenging and complex task. Current studies on article recommendation works are focused on digital libraries and reference sharing websites while studies on research social networking websites have seldom been conducted. Existing content-based approaches or collaborative filtering approaches suffer from the problem of data sparsity. The quality information of articles has been largely ignored in previous studies, thus raising the need for a unified recommendation framework. We propose a hybrid approach to combine relevance, connectivity and quality to recommend scientific articles. The effectiveness of the proposed framework and methods is verified using a user study on a real research social network website. The results demonstrate that our proposed methods outperform baseline methods.
    Type of Medium: Online Resource
    ISSN: 0165-5515 , 1741-6485
    URL: Article
    DOI: 10.1177/0165551517728449
    RVK:
    AN 10100
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2018
    detail.hit.zdb_id: 439125-1
    detail.hit.zdb_id: 2025062-9
    SSG: 24,1
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 3
    Online Resource
    Online Resource
    iLDA: An interactive latent Dirichlet allocation model to improve topic quality
    SAGE Publications ; 2020
    In:  Journal of Information Science Vol. 46, No. 1 ( 2020-02), p. 23-40
    Details
    In: Journal of Information Science, SAGE Publications, Vol. 46, No. 1 ( 2020-02), p. 23-40
    Abstract: User-generated content has been an increasingly important data source for analysing user interests in both industries and academic research. Since the proposal of the basic latent Dirichlet allocation (LDA) model, plenty of LDA variants have been developed to learn knowledge from unstructured user-generated contents. An intractable limitation for LDA and its variants is that low-quality topics whose meanings are confusing may be generated. To handle this problem, this article proposes an interactive strategy to generate high-quality topics with clear meanings by integrating subjective knowledge derived from human experts and objective knowledge learned by LDA. The proposed interactive latent Dirichlet allocation (iLDA) model develops deterministic and stochastic approaches to obtain subjective topic-word distribution from human experts, combines the subjective and objective topic-word distributions by a linear weighted-sum method, and provides the inference process to draw topics and words from a comprehensive topic-word distribution. The proposed model is a significant effort to integrate human knowledge with LDA-based models by interactive strategy. The experiments on two real-world corpora show that the proposed iLDA model can draw high-quality topics with the assistance of subjective knowledge from human experts. It is robust under various conditions and offers fundamental supports for the applications of LDA-based topic modelling.
    Type of Medium: Online Resource
    ISSN: 0165-5515 , 1741-6485
    URL: Article
    DOI: 10.1177/0165551518822455
    RVK:
    AN 10100
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2020
    detail.hit.zdb_id: 439125-1
    detail.hit.zdb_id: 2025062-9
    SSG: 24,1
    Location Call Number Limitation Availability
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    Online Resource
  • 4
    Online Resource
    Online Resource
    Sequential patent trading recommendation using knowledge-aware attentional bidirectional long short-term memory network (KBiLSTM)
    SAGE Publications ; 2023
    In:  Journal of Information Science Vol. 49, No. 3 ( 2023-06), p. 814-830
    Details
    In: Journal of Information Science, SAGE Publications, Vol. 49, No. 3 ( 2023-06), p. 814-830
    Abstract: With the rapid development of the patent marketplace, patent trading recommendation is required to mitigate the technology searching cost of patent buyers. Current research focuses on the recommendation based on existing patents of a company; a few studies take into account the sequential pattern of patent acquisition activities and the possible diversity of a company’s business interests. Moreover, the profiling of patents based on solely patent documents fails to capture the high-order information of patents. To bridge the gap, we propose a knowledge-aware attentional bidirectional long short-term memory network (KBiLSTM) method for patent trading recommendation. KBiLSTM uses knowledge graph embeddings to profile patents with rich patent information. It introduces bidirectional long short-term memory network (BiLSTM) to capture the sequential pattern in a company’s historical records. In addition, to address a company’s diverse technology interests, we design an attention mechanism to aggregate the company’s historical patents given a candidate patent. Experimental results on the United States Patent and Trademark Office (USPTO) data set show that KBiLSTM outperforms state-of-the-art baselines for patent trading recommendation in terms of F1 and normalised discounted cumulative gain (nDCG). The attention visualisation of randomly selected company intuitively demonstrates the recommendation effectiveness.
    Type of Medium: Online Resource
    ISSN: 0165-5515 , 1741-6485
    URL: Article
    DOI: 10.1177/01655515211023937
    RVK:
    AN 10100
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2023
    detail.hit.zdb_id: 2025062-9
    SSG: 24,1
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
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