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  • × author_ss:"Chen, H."
  1. Zheng, R.; Li, J.; Chen, H.; Huang, Z.: ¬A framework for authorship identification of online messages : writing-style features and classification techniques (2006) 0.04
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    Abstract
    With the rapid proliferation of Internet technologies and applications, misuse of online messages for inappropriate or illegal purposes has become a major concern for society. The anonymous nature of online-message distribution makes identity tracing a critical problem. We developed a framework for authorship identification of online messages to address the identity-tracing problem. In this framework, four types of writing-style features (lexical, syntactic, structural, and content-specific features) are extracted and inductive learning algorithms are used to build feature-based classification models to identify authorship of online messages. To examine this framework, we conducted experiments on English and Chinese online-newsgroup messages. We compared the discriminating power of the four types of features and of three classification techniques: decision trees, backpropagation neural networks, and support vector machines. The experimental results showed that the proposed approach was able to identify authors of online messages with satisfactory accuracy of 70 to 95%. All four types of message features contributed to discriminating authors of online messages. Support vector machines outperformed the other two classification techniques in our experiments. The high performance we achieved for both the English and Chinese datasets showed the potential of this approach in a multiple-language context.
    Date
    22. 7.2006 16:14:37
    Language
    e
  2. Chung, W.; Chen, H.: Browsing the underdeveloped Web : an experiment on the Arabic Medical Web Directory (2009) 0.02
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    Date
    22. 3.2009 17:57:50
    Language
    e
  3. Carmel, E.; Crawford, S.; Chen, H.: Browsing in hypertext : a cognitive study (1992) 0.02
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    Language
    e
    Source
    IEEE transactions on systems, man and cybernetics. 22(1992) no.5, S.865-884
  4. 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
    Language
    e
  5. 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
    Language
    e
  6. Chen, H.; Chau, M.: Web mining : machine learning for Web applications (2003) 0.01
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    Abstract
    With more than two billion pages created by millions of Web page authors and organizations, the World Wide Web is a tremendously rich knowledge base. The knowledge comes not only from the content of the pages themselves, but also from the unique characteristics of the Web, such as its hyperlink structure and its diversity of content and languages. Analysis of these characteristics often reveals interesting patterns and new knowledge. Such knowledge can be used to improve users' efficiency and effectiveness in searching for information an the Web, and also for applications unrelated to the Web, such as support for decision making or business management. The Web's size and its unstructured and dynamic content, as well as its multilingual nature, make the extraction of useful knowledge a challenging research problem. Furthermore, the Web generates a large amount of data in other formats that contain valuable information. For example, Web server logs' information about user access patterns can be used for information personalization or improving Web page design.
    Language
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  7. Qin, J.; Zhou, Y.; Chau, M.; Chen, H.: Multilingual Web retrieval : an experiment in English-Chinese business intelligence (2006) 0.01
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    Abstract
    As increasing numbers of non-English resources have become available on the Web, the interesting and important issue of how Web users can retrieve documents in different languages has arisen. Cross-language information retrieval (CLIP), the study of retrieving information in one language by queries expressed in another language, is a promising approach to the problem. Cross-language information retrieval has attracted much attention in recent years. Most research systems have achieved satisfactory performance on standard Text REtrieval Conference (TREC) collections such as news articles, but CLIR techniques have not been widely studied and evaluated for applications such as Web portals. In this article, the authors present their research in developing and evaluating a multilingual English-Chinese Web portal that incorporates various CLIP techniques for use in the business domain. A dictionary-based approach was adopted and combines phrasal translation, co-occurrence analysis, and pre- and posttranslation query expansion. The portal was evaluated by domain experts, using a set of queries in both English and Chinese. The experimental results showed that co-occurrence-based phrasal translation achieved a 74.6% improvement in precision over simple word-byword translation. When used together, pre- and posttranslation query expansion improved the performance slightly, achieving a 78.0% improvement over the baseline word-by-word translation approach. In general, applying CLIR techniques in Web applications shows promise.
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  8. Vishwanath, A.; Chen, H.: Technology clusters : using multidimensional scaling to evaluate and structure technology clusters (2006) 0.01
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    Abstract
    Empirical evidence suggests that the ownership of related products that form a technology cluster is signifIcantly better than the attributes of an innovation at predicting adoption. The treatment of technology clusters, however, has been ad hoc and study specific: Researchers often make a priori assumptions about the relationships between technologies and measure ownership using lists of functionally related technology, without any systematic reasoning. Hence, the authors set out to examine empirically the composition of technology clusters and the differences, if any, in clusters of technologies formed by adopters and nonadopters. Using the Galileo system of multidimensional scaling and the associational diffusion framework, the dissimilarities between 30 technology concepts were scored by adopters and nonadopters. Results indicate clear differences in conceptualization of clusters: Adopters tend to relate technologies based an their functional similarity; here, innovations are perceived to be complementary, and hence, adoption of one technology spurs the adoption of related technologies. On the other hand, nonadopters tend to relate technologies using a stricter ascendancy of association where the adoption of an innovation makes subsequent innovations redundant. The results question the measurement approaches and present an alternative methodology.
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  9. Chen, H.: Knowledge-based document retrieval : framework and design (1992) 0.00
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  10. Chen, H.: Generating, integrating and activating thesauri for concept-based document retrieval (1993) 0.00
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  11. Chen, H.; Lynch, K.J.; Bashu, K.; Ng, T.D.: Generating, integrating, and activating thesauri for concept-based document retrieval (1993) 0.00
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  12. Dumais, S.; Chen, H.: Hierarchical classification of Web content (2000) 0.00
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  13. Schatz, B.R.; Johnson, E.H.; Cochrane, P.A.; Chen, H.: Interactive term suggestion for users of digital libraries : using thesauri and co-occurrence lists for information retrieval (1996) 0.00
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  14. Huang, Z.; Chung, Z.W.; Chen, H.: ¬A graph model for e-commerce recommender systems (2004) 0.00
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  15. Chen, H.; Chung, W.; Qin, J.; Reid, E.; Sageman, M.; Weimann, G.: Uncovering the dark Web : a case study of Jihad on the Web (2008) 0.00
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  16. 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) 0.00
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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.
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  17. Chen, H.; Dhar, V.: Cognitive process as a basis for intelligent retrieval system design (1991) 0.00
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  18. Chen, H.: Explaining and alleviating information management indeterminism : a knowledge-based framework (1994) 0.00
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  19. Chung, W.; Chen, H.; Reid, E.: Business stakeholder analyzer : an experiment of classifying stakeholders on the Web (2009) 0.00
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  20. Chau, M.; Wong, C.H.; Zhou, Y.; Qin, J.; Chen, H.: Evaluating the use of search engine development tools in IT education (2010) 0.00
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    Abstract
    It is important for education in computer science and information systems to keep up to date with the latest development in technology. With the rapid development of the Internet and the Web, many schools have included Internet-related technologies, such as Web search engines and e-commerce, as part of their curricula. Previous research has shown that it is effective to use search engine development tools to facilitate students' learning. However, the effectiveness of these tools in the classroom has not been evaluated. In this article, we review the design of three search engine development tools, SpidersRUs, Greenstone, and Alkaline, followed by an evaluation study that compared the three tools in the classroom. In the study, 33 students were divided into 13 groups and each group used the three tools to develop three independent search engines in a class project. Our evaluation results showed that SpidersRUs performed better than the two other tools in overall satisfaction and the level of knowledge gained in their learning experience when using the tools for a class project on Internet applications development.
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