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  • × author_ss:"Chen, H."
  1. Vishwanath, A.; Chen, H.: Personal communication technologies as an extension of the self : a cross-cultural comparison of people's associations with technology and their symbolic proximity with others (2008) 0.02
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    Abstract
    Increasingly, individuals use communication technologies such as e-mail, IMs, blogs, and cell phones to locate, learn about, and communicate with one another. Not much, however, is known about how individuals relate to various personal technologies, their preferences for each, or their extensional associations with them. Even less is known about the cultural differences in these preferences. The current study used the Galileo system of multidimensional scaling to systematically map the extensional associations with nine personal communication technologies across three cultures: U.S., Germany, and Singapore. Across the three cultures, the technologies closest to the self were similar, suggesting a universality of associations with certain technologies. In contrast, the technologies farther from the self were significantly different across cultures. Moreover, the magnitude of associations with each technology differed based on the extensional association or distance from the self. Also, and more importantly, the antecedents to these associations differed significantly across cultures, suggesting a stronger influence of cultural norms on personal-technology choice.
  2. Huang, C.; Fu, T.; Chen, H.: Text-based video content classification for online video-sharing sites (2010) 0.01
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    Abstract
    With the emergence of Web 2.0, sharing personal content, communicating ideas, and interacting with other online users in Web 2.0 communities have become daily routines for online users. User-generated data from Web 2.0 sites provide rich personal information (e.g., personal preferences and interests) and can be utilized to obtain insight about cyber communities and their social networks. Many studies have focused on leveraging user-generated information to analyze blogs and forums, but few studies have applied this approach to video-sharing Web sites. In this study, we propose a text-based framework for video content classification of online-video sharing Web sites. Different types of user-generated data (e.g., titles, descriptions, and comments) were used as proxies for online videos, and three types of text features (lexical, syntactic, and content-specific features) were extracted. Three feature-based classification techniques (C4.5, Naïve Bayes, and Support Vector Machine) were used to classify videos. To evaluate the proposed framework, user-generated data from candidate videos, which were identified by searching user-given keywords on YouTube, were first collected. Then, a subset of the collected data was randomly selected and manually tagged by users as our experiment data. The experimental results showed that the proposed approach was able to classify online videos based on users' interests with accuracy rates up to 87.2%, and all three types of text features contributed to discriminating videos. Support Vector Machine outperformed C4.5 and Naïve Bayes techniques in our experiments. In addition, our case study further demonstrated that accurate video-classification results are very useful for identifying implicit cyber communities on video-sharing Web sites.
  3. Chung, W.; Chen, H.: Browsing the underdeveloped Web : an experiment on the Arabic Medical Web Directory (2009) 0.01
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    Date
    22. 3.2009 17:57:50
  4. Carmel, E.; Crawford, S.; Chen, H.: Browsing in hypertext : a cognitive study (1992) 0.01
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    Source
    IEEE transactions on systems, man and cybernetics. 22(1992) no.5, S.865-884
  5. Leroy, G.; Chen, H.: Genescene: an ontology-enhanced integration of linguistic and co-occurrence based relations in biomedical texts (2005) 0.01
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    Date
    22. 7.2006 14:26:01
  6. Zheng, R.; Li, J.; Chen, H.; Huang, Z.: ¬A framework for authorship identification of online messages : writing-style features and classification techniques (2006) 0.01
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    Date
    22. 7.2006 16:14:37
  7. Hu, D.; Kaza, S.; Chen, H.: Identifying significant facilitators of dark network evolution (2009) 0.01
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    Date
    22. 3.2009 18:50:30