Search (13 results, page 1 of 1)

  • × author_ss:"Wang, J."
  1. Shen, R.; Wang, J.; Fox, E.A.: ¬A Lightweight Protocol between Digital Libraries and Visualization Systems (2002) 0.01 
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    Date
    22. 2.2003 17:25:39
    22. 2.2003 18:15:14
  2. Wang, J.; Halffman, W.; Zhang, Y.H.: Sorting out journals : the proliferation of journal lists in China (2023) 0.01 
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    Abstract
    Journal lists are instruments to categorize, compare, and assess research and scholarly publications. Our study investigates the remarkable proliferation of such journal lists in China, analyses their underlying values, quality criteria and ranking principles, and specifies how concerns specific to the Chinese research policy and publishing system inform these lists. Discouraged lists of "bad journals" reflect concerns over inferior research publications, but also the involved drain on public resources. Endorsed lists of "good journals" are based on criteria valued in research policy, reflecting the distinctive administrative logic of state-led Chinese research and publishing policy, ascribing worth to scientific journals for its specific national and institutional needs. In this regard, the criteria used for journal list construction are contextual and reflect the challenges of public resource allocation in a market-led publication system. Chinese journal lists therefore reflect research policy changes, such as a shift away from output-dominated research evaluation, the specific concerns about research misconduct, and balancing national research needs against international standards, resulting in distinctly Chinese quality criteria. However, contrasting concerns and inaccuracies lead to contradictions in the "qualify" and "disqualify" binary logic and demonstrate inherent tensions and limitations in journal lists as policy tools.
    Date
    22. 9.2023 16:39:23
  3. Oard, D.W.; He, D.; Wang, J.: User-assisted query translation for interactive cross-language information retrieval (2008) 0.00 
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    Abstract
    Interactive Cross-Language Information Retrieval (CLIR), a process in which searcher and system collaborate to find documents that satisfy an information need regardless of the language in which those documents are written, calls for designs in which synergies between searcher and system can be leveraged so that the strengths of one can cover weaknesses of the other. This paper describes an approach that employs user-assisted query translation to help searchers better understand the system's operation. Supporting interaction and interface designs are introduced, and results from three user studies are presented. The results indicate that experienced searchers presented with this new system evolve new search strategies that make effective use of the new capabilities, that they achieve retrieval effectiveness comparable to results obtained using fully automatic techniques, and that reported satisfaction with support for cross-language searching increased. The paper concludes with a description of a freely available interactive CLIR system that incorporates lessons learned from this research.
  4. Hicks, D.; Wang, J.: Coverage and overlap of the new social sciences and humanities journal lists (2011) 0.00 
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    Date
    22. 1.2011 13:21:28
  5. Gauch, S.; Wang, J.: Corpus analysis for TREC 5 query expansion (1997) 0.00 
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    Source
    The Fifth Text Retrieval Conference (TREC-5). Ed.: E.M. Voorhees u. D.K. Harman
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  6. He, R.; Wang, J.; Tian, J.; Chu, C.-T.; Mauney, B.; Perisic, I.: Session analysis of people search within a professional social network (2013) 0.00 
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    Date
    19. 4.2013 20:31:22
  7. Jiang, Z.; Gu, Q.; Yin, Y.; Wang, J.; Chen, D.: GRAW+ : a two-view graph propagation method with word coupling for readability assessment (2019) 0.00 
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    Date
    15. 4.2019 13:46:22
  8. Strzalkowski, T.; Guthrie, L.; Karlgren, J.; Leistensnider, J.; Lin, F.; Perez-Carballo, J.; Straszheim, T.; Wang, J.; Wilding, J.: Natural language information retrieval : TREC-5 report (1997) 0.00 
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    Source
    The Fifth Text Retrieval Conference (TREC-5). Ed.: E.M. Voorhees u. D.K. Harman
  9. Wang, J.; Oard, D.W.: Matching meaning for cross-language information retrieval (2012) 0.00 
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    Abstract
    This article describes a framework for cross-language information retrieval that efficiently leverages statistical estimation of translation probabilities. The framework provides a unified perspective into which some earlier work on techniques for cross-language information retrieval based on translation probabilities can be cast. Modeling synonymy and filtering translation probabilities using bidirectional evidence are shown to yield a balance between retrieval effectiveness and query-time (or indexing-time) efficiency that seems well suited large-scale applications. Evaluations with six test collections show consistent improvements over strong baselines.
  10. Wang, J.; Reid, E.O.F.: Developing WWW information systems on the Internet (1996) 0.00 
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    Abstract
    Gives an overview of Web information system development. Discusses some basic concepts and technologies such as HTML, HTML FORM, CGI and Java, which are associated with developing WWW information systems. Further discusses the design and implementation of Virtual Travel Mart, a Web based end user oriented travel information system. Finally, addresses some issues in developing WWW information systems
  11. Mao, J.; Xu, W.; Yang, Y.; Wang, J.; Yuille, A.L.: Explain images with multimodal recurrent neural networks (2014) 0.00 
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    Abstract
    In this paper, we present a multimodal Recurrent Neural Network (m-RNN) model for generating novel sentence descriptions to explain the content of images. It directly models the probability distribution of generating a word given previous words and the image. Image descriptions are generated by sampling from this distribution. The model consists of two sub-networks: a deep recurrent neural network for sentences and a deep convolutional network for images. These two sub-networks interact with each other in a multimodal layer to form the whole m-RNN model. The effectiveness of our model is validated on three benchmark datasets (IAPR TC-12 [8], Flickr 8K [28], and Flickr 30K [13]). Our model outperforms the state-of-the-art generative method. In addition, the m-RNN model can be applied to retrieval tasks for retrieving images or sentences, and achieves significant performance improvement over the state-of-the-art methods which directly optimize the ranking objective function for retrieval.
  12. Wang, J.; Clements, M.; Yang, J.; Vries, A.P. de; Reinders, M.J.T.: Personalization of tagging systems (2010) 0.00 
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    Abstract
    Social media systems have encouraged end user participation in the Internet, for the purpose of storing and distributing Internet content, sharing opinions and maintaining relationships. Collaborative tagging allows users to annotate the resulting user-generated content, and enables effective retrieval of otherwise uncategorised data. However, compared to professional web content production, collaborative tagging systems face the challenge that end-users assign tags in an uncontrolled manner, resulting in unsystematic and inconsistent metadata. This paper introduces a framework for the personalization of social media systems. We pinpoint three tasks that would benefit from personalization: collaborative tagging, collaborative browsing and collaborative search. We propose a ranking model for each task that integrates the individual user's tagging history in the recommendation of tags and content, to align its suggestions to the individual user preferences. We demonstrate on two real data sets that for all three tasks, the personalized ranking should take into account both the user's own preference and the opinion of others.
  13. Wang, J.: Automatic thesaurus development : term extraction from title metadata (2006) 0.00 
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    Abstract
    The application of thesauri in networked environments is seriously hampered by the challenges of introducing new concepts and terminology into the formal controlled vocabulary, which is critical for enhancing its retrieval capability. The author describes an automated process of adding new terms to thesauri as entry vocabulary by analyzing the association between words/phrases extracted from bibliographic titles and subject descriptors in the metadata record (subject descriptors are terms assigned from controlled vocabularies of thesauri to describe the subjects of the objects [e.g., books, articles] represented by the metadata records). The investigated approach uses a corpus of metadata for scientific and technical (S&T) publications in which the titles contain substantive words for key topics. The three steps of the method are (a) extracting words and phrases from the title field of the metadata; (b) applying a method to identify and select the specific and meaningful keywords based on the associated controlled vocabulary terms from the thesaurus used to catalog the objects; and (c) inserting selected keywords into the thesaurus as new terms (most of them are in hierarchical relationships with the existing concepts), thereby updating the thesaurus with new terminology that is being used in the literature. The effectiveness of the method was demonstrated by an experiment with the Chinese Classification Thesaurus (CCT) and bibliographic data in China Machine-Readable Cataloging Record (MARC) format (CNMARC) provided by Peking University Library. This approach is equally effective in large-scale collections and in other languages.

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