Article
Computer Science, Information Systems
Ming Li, Yating Ma, Ying Li, Yixue Bai
Summary: This paper proposes a multimodal representative answer extraction method to solve the information overload problem in community question answering. The method uses multimodal clustering and an optimization algorithm to extract a representative subset of answers. Experimental results demonstrate the effectiveness of the proposed method.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2023)
Article
Computer Science, Information Systems
Lingfei Qian, Jian Wang, Hongfei Lin, Liang Yang
Summary: Answer ranking is crucial in CQA systems, and existing methods mainly learn respondents' expertise from history answers, ignoring structure correlations between question raisers and respondents. To address this, the proposed MPRR network employs a HIN to preserve structure correlations and uses a pre-trained language model to learn respondents' expertise more efficiently. The model outperforms all baseline models across three real-world datasets in terms of ranking metrics.
INFORMATION SCIENCES
(2023)
Article
Environmental Studies
Hengyun Li, Hongbo Liu, Hyejo Hailey Shin, Haipeng Ji
Summary: This study examines the effects of customer-generated images in online reviews on subsequent customer engagement, using computer vision technique and panel data analysis. Findings reveal that the ratio of pictorial reviews positively influences review volume and average review length, while the disparity between review text and photo sentiment has a complex impact on customer engagement. Business price level can mitigate these effects.
TOURISM MANAGEMENT
(2024)
Article
Computer Science, Artificial Intelligence
Fengshi Jing, Hao Ren, Weibin Cheng, Xin Wang, Qingpeng Zhang
Summary: In a community question-answering (CQA) system, the best answer for a specific question plays a key role in improving service quality. Existing approaches to answer selection in CQA systems have limitations in incorporating both expertise and authority of the respondents. In this study, a new model called KAAS is proposed to enhance performance by considering both expertise and authority, utilizing domain knowledge, and integrating social network information.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Automation & Control Systems
Binbin Jin, Enhong Chen, Hongke Zhao, Zhenya Huang, Qi Liu, Hengshu Zhu, Shui Yu
Summary: In this paper, a unified model EARNN is proposed for answer selection and ranking tasks in CQA. The model leverages both Q&A semantics and multifacet domain effects, with attention mechanisms designed to capture deep effects of topics and a time-sensitive ranking function to model timeliness in CQA. A question-dependent pairwise learning strategy is also developed to effectively train the model, and experimental results on a real-world dataset from Quora validate its effectiveness and interpretability.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Qing Liu, Trong Dinh Thac Do, Longbing Cao
Summary: This article introduces a novel statistical model (MAGIC) for automatically generating answer keywords in CQA. MAGIC can efficiently generate answer keywords for both existing and new questions, outperforming other models in recommending appropriate and informative answer keywords.
IEEE INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Information Systems
B. Athira, Sumam Mary Idicula, Josette Jones, Anand Kulanthaivel
Summary: Health community forums serve as online platforms for discussing illness management. When diagnosed with life-threatening diseases like cancer, people increasingly turn to these platforms for answers. This paper proposes an answer recommendation system in an online breast cancer community forum to guide users and provide valuable references for decision-making.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Review
Environmental Studies
Mingming Hu, Hengyun Li, Haiyan Song, Xin Li, Rob Law
Summary: This study aims to forecast international tourist arrivals to Hong Kong from seven English-speaking countries. Incorporating tourist-generated online review data into the destination forecasting system, the study presents a new direction in tourism demand modeling and forecasting. The empirical findings indicate that using tourists' online review data can significantly improve the performance of tourism demand models, particularly when high-frequency online review data is included in traditional time-series models.
TOURISM MANAGEMENT
(2022)
Article
Computer Science, Artificial Intelligence
Pradeep Kumar Roy
Summary: Stack Exchange is a popular community question answering site. This paper proposed a deep learning-based framework to predict the virtual votes for answers in order to address the issue of new answers being overlooked in the list, and motivate users to post high-quality answers.
NEURAL PROCESSING LETTERS
(2021)
Article
Computer Science, Artificial Intelligence
Golshan Afzali Boroujeni, Heshaam Faili, Yadollah Yaghoobzadeh
Summary: This paper proposes a novel method for answer selection in community question answering (CQA) by utilizing knowledge from knowledge graphs (KGs). The paper also introduces a latent-variable model for learning question and answer representations, and uses variational autoencoders (VAE) in a multi-task learning process to generate class-specific representations for answers. Experimental results demonstrate the effectiveness of the proposed method.
Article
Computer Science, Software Engineering
Ifeanyi G. Ndukwe, Sherlock A. Licorish, Stephen G. MacDonell
Summary: Software developers use crowdsourcing during development for collaboration and learning from others. However, little is known about their experiences on online platforms, particularly in solving encountered problems. Our study fills this gap by interviewing 50 practitioners, showing that online portals are crucial to modern software development, providing timely code solutions and debugging assistance, but also presenting potential negative experiences that could harm the community. We discuss implications like improving code search, validation, and attribution to address these findings.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2023)
Article
Health Care Sciences & Services
PengFei Li, Lin Xu, Tingting Tang, Xiaoqian Wu, Cheng Huang
Summary: This study analyzed the influencing factors of SQAC users' willingness to adopt health information and found that performance expectation, social influence, and facilitating conditions positively affected users' willingness. The results suggested that gender had a significant moderating effect on users' willingness to adopt health information.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2021)
Article
Information Science & Library Science
Chen Chen, Dylan Walker
Summary: Online health question-and-answer platforms have become important channels for patients in China to seek medical advice. A study of a popular platform, 120ask.com, found that the overall quality of medical advice was high, but patients lacked the ability to accurately evaluate the advice. Evaluation accuracy was worse for critical categories and vulnerable subpopulations.
INFORMATION SYSTEMS RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Sabine Friedel, Barbara Felderer, Ulrich Krieger, Carina Cornesse, Annelies G. Blom
Summary: This study investigates the effectiveness of early bird cash incentives in recruiting sample units for online panels. The findings show that offering early bird cash incentives significantly increases panel response rates, accelerates fieldwork progress, reduces reminders, and improves cost-effectiveness. Moreover, the sample representativeness remains high with or without early bird incentives.
SOCIAL SCIENCE COMPUTER REVIEW
(2023)
Article
Economics
Mary A. Burke, Ali Ozdagli
Summary: Recent research has shown mixed results on the relationship between inflation expectations and consumption, using qualitative measures of readiness to spend. This study uses survey panel data from the United States between 2009 and 2012 to reexamine this question and control for household heterogeneity. The findings suggest that expected inflation only increases durables spending for certain types of households, while nondurables spending does not respond to expected inflation. Furthermore, spending decreases with expected unemployment. These results indicate a limited stimulating effect of inflation expectations on aggregate consumption, which could be reversed if inflation and unemployment expectations change together.
REVIEW OF ECONOMICS AND STATISTICS
(2023)
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Surgery
Ibrahim Khansa, Lara Khansa, Gregory D. Pearson
AESTHETIC SURGERY JOURNAL
(2016)
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Surgery
Ibrahim Khansa, Lara Khansa, Gregory D. Pearson
PLASTIC AND RECONSTRUCTIVE SURGERY
(2016)
Review
Surgery
Jeffrey E. Janis, Lara Khansa, Ibrahim Khansa
PLASTIC AND RECONSTRUCTIVE SURGERY
(2016)
Article
Health Policy & Services
Zachary Davis, Lara Khansa
HEALTH POLICY AND TECHNOLOGY
(2016)
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Computer Science, Information Systems
Lara Khansa, Jungwon Kuem, Mikko Siponen, Sung S. Kim
JOURNAL OF MANAGEMENT INFORMATION SYSTEMS
(2017)
Article
Computer Science, Artificial Intelligence
James McWhorter, Lucas Brown, Lara Khansa
BIOLOGICALLY INSPIRED COGNITIVE ARCHITECTURES
(2017)
Article
Surgery
Ibrahim Khansa, Lara Khansa, Tormod S. Westvik, Jamil Ahmad, Frank Lista, Jeffrey E. Janis
PLASTIC AND RECONSTRUCTIVE SURGERY
(2018)
Article
Computer Science, Interdisciplinary Applications
Christopher W. Zobel, Lara Khansa
COMPUTERS & OPERATIONS RESEARCH
(2014)
Article
Computer Science, Information Systems
Lara Khansa, Christopher W. Zobel
JOURNAL OF COMPUTER INFORMATION SYSTEMS
(2014)
Article
Health Care Sciences & Services
Jason Dominiczak, Lara Khansa
JOINT COMMISSION JOURNAL ON QUALITY AND PATIENT SAFETY
(2018)
Article
Information Science & Library Science
Jamin Casselman, Nicholas Onopa, Lara Khansa
TELEMATICS AND INFORMATICS
(2017)
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Social Issues
Lara Khansa, Zachary Davis, Heather Davis, Andrea Chin, Heather Irvine, Linda Nichols, Jeffry A. Lang, Noah MacMichael
TECHNOLOGY IN SOCIETY
(2016)
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Business, Finance
Lara Khansa
JOURNAL OF ECONOMICS AND BUSINESS
(2015)
Article
Information Science & Library Science
Lara Khansa, Reza Barkhi, Soumya Ray, Zachary Davis
INFORMATION TECHNOLOGY & MANAGEMENT
(2018)