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  • × author_ss:"Chen, H.-H."
  1. Chen, H.-H.; Lin, W.-C.; Yang, C.; Lin, W.-H.: Translating-transliterating named entities for multilingual information access (2006) 0.01 
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    Date
    4. 6.2006 19:52:22
  2. Bian, G.-W.; Chen, H.-H.: Cross-language information access to multilingual collections on the Internet (2000) 0.01 
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    Date
    16. 2.2000 14:22:39
  3. Lin, W.-C.; Chang, Y.-C.; Chen, H.-H.: Integrating textual and visual information for cross-language image retrieval : a trans-media dictionary approach (2007) 0.01 
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    Source
    Information processing and management. 43(2007) no.2, S.488-502
  4. Ku, L.-W.; Ho, H.-W.; Chen, H.-H.: Opinion mining and relationship discovery using CopeOpi opinion analysis system (2009) 0.01 
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    Abstract
    We present CopeOpi, an opinion-analysis system, which extracts from the Web opinions about specific targets, summarizes the polarity and strength of these opinions, and tracks opinion variations over time. Objects that yield similar opinion tendencies over a certain time period may be correlated due to the latent causal events. CopeOpi discovers relationships among objects based on their opinion-tracking plots and collocations. Event bursts are detected from the tracking plots, and the strength of opinion relationships is determined by the coverage of these plots. To evaluate opinion mining, we use the NTCIR corpus annotated with opinion information at sentence and document levels. CopeOpi achieves sentence- and document-level f-measures of 62% and 74%. For relationship discovery, we collected 1.3M economics-related documents from 93 Web sources over 22 months, and analyzed collocation-based, opinion-based, and hybrid models. We consider as correlated company pairs that demonstrate similar stock-price variations, and selected these as the gold standard for evaluation. Results show that opinion-based and collocation-based models complement each other, and that integrated models perform the best. The top 25, 50, and 100 pairs discovered achieve precision rates of 1, 0.92, and 0.79, respectively.
  5. Hsu, M.-H.; Chen, H.-H.: Efficient and effective prediction of social tags to enhance Web search (2011) 0.00 
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    Abstract
    As the web has grown into an integral part of daily life, social annotation has become a popular manner for web users to manage resources. This method of management has many potential applications, but it is limited in applicability by the cold-start problem, especially for new resources on the web. In this article, we study automatic tag prediction for web pages comprehensively and utilize the predicted tags to improve search performance. First, we explore the stabilizing phenomenon of tag usage in a social bookmarking system. Then, we propose a two-stage tag prediction approach, which is efficient and is effective in making use of early annotations from users. In the first stage, content-based ranking, candidate tags are selected and ranked to generate an initial tag list. In the second stage, random-walk re-ranking, we adopt a random-walk model that utilizes tag co-occurrence information to re-rank the initial list. The experimental results show that our algorithm effectively proposes appropriate tags for target web pages. In addition, we present a framework to incorporate tag prediction in a general web search. The experimental results of the web search validate the hypothesis that the proposed framework significantly enhances the typical retrieval model.
  6. Tsai, M.-.F.; Chen, H.-H.; Wang, Y.-T.: Learning a merge model for multilingual information retrieval (2011) 0.00 
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    Source
    Information processing and management. 47(2011) no.5, S.635-646

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