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He, R.; Wang, J.; Tian, J.; Chu, C.-T.; Mauney, B.; Perisic, I.: Session analysis of people search within a professional social network (2013)
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- Abstract
- We perform session analysis for our domain of people search within a professional social network. We find that the content-based method is appropriate to serve as a basis for the session identification in our domain. However, there remain some problems reported in previous research which degrade the identification performance (such as accuracy) of the content-based method. Therefore, in this article, we propose two important refinements to address these problems. We describe the underlying rationale of our refinements and then empirically show that the content-based method equipped with our refinements is able to achieve an excellent identification performance in our domain (such as 99.820% accuracy and 99.707% F-measure in our experiments). Next, because the time-based method has extremely low computation costs, which makes it suitable for many real-world applications, we investigate the feasibility of the time-based method in our domain by evaluating its identification performance based on our refined content-based method. Our experiments demonstrate that the performance of the time-based method is potentially acceptable to many real applications in our domain. Finally, we analyze several features of the identified sessions in our domain and compare them with the corresponding ones in general web search. The results illustrate the profession-oriented characteristics of our domain.
- Date
- 19. 4.2013 20:31:22
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Wang, J.; Reid, E.O.F.: Developing WWW information systems on the Internet (1996)
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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
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Lu, C.; Bu, Y.; Wang, J.; Ding, Y.; Torvik, V.; Schnaars, M.; Zhang, C.: Examining scientific writing styles from the perspective of linguistic complexity : a cross-level moderation model (2019)
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- Abstract
- Publishing articles in high-impact English journals is difficult for scholars around the world, especially for non-native English-speaking scholars (NNESs), most of whom struggle with proficiency in English. To uncover the differences in English scientific writing between native English-speaking scholars (NESs) and NNESs, we collected a large-scale data set containing more than 150,000 full-text articles published in PLoS between 2006 and 2015. We divided these articles into three groups according to the ethnic backgrounds of the first and corresponding authors, obtained by Ethnea, and examined the scientific writing styles in English from a two-fold perspective of linguistic complexity: (a) syntactic complexity, including measurements of sentence length and sentence complexity; and (b) lexical complexity, including measurements of lexical diversity, lexical density, and lexical sophistication. The observations suggest marginal differences between groups in syntactical and lexical complexity.
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Wang, J.: ¬An extensive study on automated Dewey Decimal Classification (2009)
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- Abstract
- In this paper, we present a theoretical analysis and extensive experiments on the automated assignment of Dewey Decimal Classification (DDC) classes to bibliographic data with a supervised machine-learning approach. Library classification systems, such as the DDC, impose great obstacles on state-of-art text categorization (TC) technologies, including deep hierarchy, data sparseness, and skewed distribution. We first analyze statistically the document and category distributions over the DDC, and discuss the obstacles imposed by bibliographic corpora and library classification schemes on TC technology. To overcome these obstacles, we propose an innovative algorithm to reshape the DDC structure into a balanced virtual tree by balancing the category distribution and flattening the hierarchy. To improve the classification effectiveness to a level acceptable to real-world applications, we propose an interactive classification model that is able to predict a class of any depth within a limited number of user interactions. The experiments are conducted on a large bibliographic collection created by the Library of Congress within the science and technology domains over 10 years. With no more than three interactions, a classification accuracy of nearly 90% is achieved, thus providing a practical solution to the automatic bibliographic classification problem.
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Shen, R.; Wang, J.; Fox, E.A.: ¬A Lightweight Protocol between Digital Libraries and Visualization Systems (2002)
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- Date
- 22. 2.2003 17:25:39
22. 2.2003 18:15:14
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Wang, J.; Clements, M.; Yang, J.; Vries, A.P. de; Reinders, M.J.T.: Personalization of tagging systems (2010)
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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.
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Thomas, I.S.; Wang, J.; GPT-3: Was euch zu Menschen macht : Antworten einer künstlichen Intelligenz auf die großen Fragen des Lebens (2022)
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- Date
- 7. 1.2023 18:41:29
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Hicks, D.; Wang, J.: Coverage and overlap of the new social sciences and humanities journal lists (2011)
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- Date
- 22. 1.2011 13:21:28
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Jiang, Z.; Gu, Q.; Yin, Y.; Wang, J.; Chen, D.: GRAW+ : a two-view graph propagation method with word coupling for readability assessment (2019)
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- Date
- 15. 4.2019 13:46:22
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Wang, J.; Halffman, W.; Zhang, Y.H.: Sorting out journals : the proliferation of journal lists in China (2023)
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- Date
- 22. 9.2023 16:39:23
