Browsing by Author "Chen, Yu-Hsuan"

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Complementary QA Network Analysis for QA Retrieval in Social Question-Answering Websites
(2015-01-01)
Liu, Duen-Ren
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Chen, Yu-Hsuan
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Shen, Minxin
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Lu, Pei-Jung
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資訊管理與財務金融系註：原資管所+財金所
With the ubiquity of the Internet and the rapid development of Web 2.0 technology, social question and answering (SQA) websites have become popular knowledge-sharing platforms. As the number of posted questions and answers (QAs) continues to increase rapidly, the massive amount of question-answer knowledge is causing information overload. The problem is compounded by the growing number of redundant QAs. SQA websites such as Yahoo! Answers are open platforms where users can freely ask or answer questions. Users also may wish to learn more about the information provided in an answer so they can use related keywords in the answer to search for extended, complementary information. In this article, we propose a novel approach to identify complementary QAs (CQAs) of a target QA. We define two types of complementarity: partial complementarity and extended complementarity. First, we utilize a classification-based approach to predict complementary relationships between QAs based on three measures: question similarity, answer novelty, and answer correlation. Then we construct a CQA network based on the derived complementary relationships. In addition, we introduce a CQA network analysis technique that searches the QA network to find direct and indirect CQAs of the target QA. The results of experiments conducted on the data collected from Yahoo! Answers Taiwan show that the proposed approach can more effectively identify CQAs than can the conventional similarity-based method. Case and user study results also validate the helpfulness and the effectiveness of our approach.
DESIGN OF MARINE VEHICLE POWERED BY MAGNETOHYDRODYNAMIC THRUSTER
(2020-01-01)
Chan, Cherng-Shyong
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Cheng, Jia-Hong
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Zeng, Cing-Hui
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Huang, Jen-Rung
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Chen, Yu-Hsuan
The present study outlines the design of a magnetohydrodynamic (MHD) thruster system which is capable to power a 3-meter ship model cruising at a speed of V = 0.5 m/s using the Lorentz force generated by the electric field and magnetic field in conducting seawater. Based on the computational fluid dynamics (CFD) simulation of a modified Delft 372 catamaran model, the thrust needed to achieve the targeted cruising speed is first estimated. To achieve the estimated magnitude of the thrust, dimensions of thruster modules are designed based on numerical simulations of magnetic field, for better distributions of the strength and uniformity of the magnetic field. Additional CFD simulations of the flows through the thruster module, coupled with magnetic and electric fields, are conducted to realize the hydrodynamics. Consequently, several configurations of thruster modules are manufactured and experimented. A particular configuration of a shielded two-unit module is chosen to power the ship model. Finally, a complete system of MHD-1 marine vehicle, including a ship model, multiple MHD thruster modules and power suppliers, is assembled and tested. The system is shown capable to cruise closely to the targeted speed.
Infrared Spectra of Isomers of Protonated Aniline in Solid para-Hydrogen
(2020-03-19)
Tsuge, Masashi
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Chen, Yu-Hsuan
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Lee, Yuan-Pern
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交大名義發表
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應用化學系
The protonation sites of aniline molecule play important roles in its chemical reactions, but the preferred protonation site of gaseous aniline has yet to be determined. In this work, we recorded infrared (IR) absorption spectra of three isomers of protonated aniline, H+C6H5NH2, produced on electron bombardment during matrix deposition at 3.2 K of a mixture of aniline and para-H-2. The intensities of IR lines of H+C6H5NH2 decreased during maintenance of the electron-bombarded matrix in darkness because of neutralization with electrons that were slowly released from their trapping sites. The observed lines were classified into three groups according to their behavior upon secondary photolysis with light at 375 and 254 nm and assigned to para-, amino-, and ortho-H+C6H5NH2, the three most stable isomers of protonated aniline, according to comparison of experimental spectra with quantum-chemically predicted spectra of five possible isomers of H+C6H5NH2. The spectra of para- and ortho-H+C6H5NH2 are newly distinguished. The approximate relative abundance of these isomers in solid p-H-2 was para:amino:ortho similar to (1.0 +/- 0.1):(1.0 +/- 0.6):(0.6 +/- 0.1). The possible mechanisms of formation are discussed.
Integrating expert profile, reputation and link analysis for expert finding in question-answering websites
(2013-01-01)
Liu, Duen-Ren
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Chen, Yu-Hsuan
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Kao, Wei-Chen
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Wang, Hsiu-Wen
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資訊管理與財務金融系註：原資管所+財金所
Question answering websites are becoming an ever more popular knowledge sharing platform. On such websites, people may ask any type of question and then wait for someone else to answer the question. However, in this manner, askers may not obtain correct answers from appropriate experts. Recently, various approaches have been proposed to automatically find experts in question answering websites. In this paper, we propose a novel hybrid approach to effectively find experts for the category of the target question in question answering websites. Our approach considers user subject relevance, user reputation and authority of a category in finding experts. A user's subject relevance denotes the relevance of a user's domain knowledge to the target question. A user's reputation is derived from the user's historical question-answering records, while user authority is derived from link analysis. Moreover, our proposed approach has been extended to develop a question dependent approach that considers the relevance of historical questions to the target question in deriving user domain knowledge, reputation and authority. We used a dataset obtained from Yahoo! Answer Taiwan to evaluate our approach. Our experiment results show that our proposed methods outperform other conventional methods. (C) 2012 Elsevier Ltd. All rights reserved.
Integrating expert profile, reputation and link analysis for expert finding in question-answering websites
(2013-01-01)
Liu, Duen-Ren
;
Chen, Yu-Hsuan
;
Kao, Wei-Chen
;
Wang, Hsiu-Wen
;
資訊管理與財務金融系註：原資管所+財金所
Question answering websites are becoming an ever more popular knowledge sharing platform. On such websites, people may ask any type of question and then wait for someone else to answer the question. However, in this manner, askers may not obtain correct answers from appropriate experts. Recently, various approaches have been proposed to automatically find experts in question answering websites. In this paper, we propose a novel hybrid approach to effectively find experts for the category of the target question in question answering websites. Our approach considers user subject relevance, user reputation and authority of a category in finding experts. A user's subject relevance denotes the relevance of a user's domain knowledge to the target question. A user's reputation is derived from the user's historical question-answering records, while user authority is derived from link analysis. Moreover, our proposed approach has been extended to develop a question dependent approach that considers the relevance of historical questions to the target question in deriving user domain knowledge, reputation and authority. We used a dataset obtained from Yahoo! Answer Taiwan to evaluate our approach. Our experiment results show that our proposed methods outperform other conventional methods. (C) 2012 Elsevier Ltd. All rights reserved.
QA document recommendations for communities of question-answering websites
(2014-02-01)
Liu, Duen-Ren
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Chen, Yu-Hsuan
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Huang, Chun-Kai
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資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
With the rapid development of Internet and Web 2.0 technology, Question & Answering (Q&A) websites have become an essential knowledge-sharing platform. This platform provides knowledge community services where users with common interests or expertise can form a knowledge community. Community members can collect and share QA knowledge (documents) regarding their interests. However, due to the massive amount of QAs created every day, information overload can become a major problem. Consequently, a recommendation mechanism is needed to recommend QA documents for communities of Q&A websites. Existing studies did not investigate the recommendation mechanisms for knowledge collections in communities of Q&A Websites. Traditional recommendation methods use member importance as weight to consolidate individual profiles and generate group profiles, which in turn are used to filter out items of recommendation. However, they do not consider certain factors of the recommended items, such as the reputation of the community members and the complementary relationships between documents. In this work, we propose a novel method to recommend related QA documents for knowledge communities of Q&A websites. The proposed method recommends QA documents by considering factors such as the community members' reputation in collecting and answering QAs, the push scores and collection time of QAs, the complementary relationships between QAs and their relevance to the communities. This research evaluates and compares the proposed methods using an experimental dataset collected from Yahoo! Answers Taiwan website. Experimental results show that the proposed method outperforms other conventional methods, providing a more effective manner to recommend Q&A documents to knowledge communities. (C) 2013 Elsevier B.V. All rights reserved.
Recommending QA Documents for Communities of Question-Answering Websites
(2013)
Liu, Duen-Ren
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Huang, Chun-Kai
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Chen, Yu-Hsuan
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資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Question & Answering (Q&A) websites have become an essential knowledge-sharing platform. This platform provides knowledge-community services where users with common interests or expertise can form a knowledge community to collect and share QA documents. However, due to the massive amount of QAs, information overload can become a major problem. Consequently, a recommendation mechanism is needed to recommend QAs for communities of Q&A websites. Existing studies did not investigate the recommendation mechanisms for knowledge collections in communities of Q&A Websites. In this work, we propose a novel recommendation method to recommend related QAs for communities of Q&A websites. The proposed method recommends QAs by considering the community members\' reputations, the push scores and collection time of QAs, the complementary relationships between QAs and their relevance to the communities. Experimental results show that the proposed method outperforms other conventional methods, providing a more effective manner to recommend QA documents to knowledge communities.