Access the full text.
Sign up today, get DeepDyve free for 14 days.
P. Roy, J. Singh, A. Nag (2018)
Finding Active Expert Users for Question Routing in Community Question Answering Sites
Baichuan Li, Irwin King, Michael Lyu (2011)
Question routing in community question answering: putting category in its place
M. Nouiri, A. Bekrar, Abderezak Jemai, S. Niar, A. Ammari (2018)
An effective and distributed particle swarm optimization algorithm for flexible job-shop scheduling problemJournal of Intelligent Manufacturing, 29
Kai Wang, Zhaoyan Ming, Xia Hu, Tat-Seng Chua (2010)
Segmentation of multi-sentence questions: towards effective question retrieval in cQA servicesProceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Hong Cai, Cuiting Yan, Airu Yin, Xuesong Zhao (2017)
Question Recommendation in Medical Community-Based Question Answering
K. Deb, S. Agrawal, Amrit Pratap, T. Meyarivan (2000)
A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II
Duen-Ren Liu, Yu-Hsuan Chen, Wei-Chen Kao, H. Wang (2013)
Integrating expert profile, reputation and link analysis for expert finding in question-answering websitesInf. Process. Manag., 49
Xiang Cheng, Shuguang Zhu, Sen Su, Gang Chen (2017)
A Multi-Objective Optimization Approach for Question Routing in Community Question Answering ServicesIEEE Transactions on Knowledge and Data Engineering, 29
A. Mehri, Maryam Jamaati, H. Mehri (2015)
Word ranking in a single document by Jensen–Shannon divergencePhysics Letters A, 379
C. Shah, Vanessa Kitzie (2012)
Social Q&A and virtual reference - comparing apples and oranges with the help of experts and usersJ. Assoc. Inf. Sci. Technol., 63
S. Mirjalili, Shahrzad Saremi, S. Mirjalili, L. Coelho (2016)
Multi-objective grey wolf optimizer: A novel algorithm for multi-criterion optimizationExpert Syst. Appl., 47
Jin Zhang, Guannan Liu, Ming Ren (2016)
Finding a representative subset from large-scale documentsJ. Informetrics, 10
Kai Zhang, Wei Wu, Haocheng Wu, Zhoujun Li, M. Zhou (2014)
Question Retrieval with High Quality Answers in Community Question AnsweringProceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management
N. Lynn, P. Suganthan (2017)
Ensemble particle swarm optimizerAppl. Soft Comput., 55
R. Kuo, Y. Syu, Zhen-Yao Chen, F. Tien (2012)
Integration of particle swarm optimization and genetic algorithm for dynamic clusteringInf. Sci., 195
G. Dror, Y. Koren, Y. Maarek, Idan Szpektor (2011)
I want to answer; who has a question?: Yahoo! answers recommender system
Wen Chan, Jintao Du, Weidong Yang, Jinhui Tang, Xiangdong Zhou (2014)
Term Selection and Result Reranking for Question Retrieval by Exploiting Hierarchical ClassificationProceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management
Yunbo Cao, Huizhong Duan, Chin-Yew Lin, Yong Yu, H. Hon (2008)
Recommending questions using the mdl-based tree cut model
Ivan Srba, Marek Grznar, M. Bieliková (2015)
Utilizing non-QA data to improve questions routing for users with low QA activity in CQA2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
David Arthur, Sergei Vassilvitskii (2007)
k-means++: the advantages of careful seeding
Zhou Zhao, Lijun Zhang, Xiaofei He, Wilfred Ng (2015)
Expert Finding for Question Answering via Graph Regularized Matrix CompletionIEEE Transactions on Knowledge and Data Engineering, 27
Zhe Liu, B. Jansen (2017)
Identifying and predicting the desire to help in social question and answeringInf. Process. Manag., 53
Xin Cao, G. Cong, B. Cui, Christian Jensen, Quan Yuan (2012)
Approaches to Exploring Category Information for Question Retrieval in Community Question-Answer ArchivesACM Trans. Inf. Syst., 30
G. Canfora, M. Penta, Raffaele Esposito, M. Villani (2005)
An approach for QoS-aware service composition based on genetic algorithms
Xiaohu Yan, Fazhi He, Neng Hou, H. Ai (2017)
An Efficient Particle Swarm Optimization for Large-Scale Hardware/Software Co-Design SystemInt. J. Cooperative Inf. Syst., 27
Ivan Srba, M. Bieliková (2015)
Askalot: Community Question Answering as a Means for Knowledge Sharing in an Educational OrganizationProceedings of the 18th ACM Conference Companion on Computer Supported Cooperative Work & Social Computing
Xian-Ling Mao, Yi-Jing Hao, Dan Wang, Heyan Huang (2018)
Query completion in community-based Question Answering searchNeurocomputing, 274
Mohammad Azadjalal, P. Moradi, Alireza Abdollahpouri, M. Jalili (2017)
A trust-aware recommendation method based on Pareto dominance and confidence conceptsKnowl. Based Syst., 116
C. Raquel, P. Naval (2005)
An effective use of crowding distance in multiobjective particle swarm optimization
Diego Ingaramo, David Pinto, Paolo Rosso, M. Errecalde (2008)
Evaluation of Internal Validity Measures in Short-Text Corpora
Cheng Chen, Kui Wu, Venkatesh Srinivasan, R. Bharadwaj (2012)
The best answers? Think twice: Online detection of commercial campaigns in the CQA forums2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013)
S. Hu, Y. Liu, Tupei Chen, Zengcai Liu, Q. Yu, L. Deng, Y. Yin, S. Hosaka (2013)
Emulating the Ebbinghaus forgetting curve of the human brain with a NiO-based memristorApplied Physics Letters, 103
R. Kuo, S. Lin, Zhen-Yao Chen (2015)
Integration of Particle Swarm Optimization and Immune Genetic Algorithm-Based Dynamic Clustering for Customer ClusteringInt. J. Artif. Intell. Tools, 24
Baichuan Li, Irwin King (2010)
Routing questions to appropriate answerers in community question answering servicesProceedings of the 19th ACM international conference on Information and knowledge management
A. Figueroa (2017)
Automatically generating effective search queries directly from community question-answering questions for finding related questionsExpert Syst. Appl., 77
Haocheng Wu, Wei Wu, M. Zhou, Enhong Chen, Lei Duan, Harry Shum (2014)
Improving search relevance for short queries in community question answeringProceedings of the 7th ACM international conference on Web search and data mining
Baojun Ma, Q. Wei, Guoqing Chen (2011)
A combined measure for representative information retrieval in enterprise information systemsJ. Enterp. Inf. Manag., 24
Amr Azzam, N. Tazi, A. Hossny (2017)
A Question Routing Technique Using Deep Neural Network for Communities of Question Answering
Fatemeh Riahi, Zainab Zolaktaf, Mahdi Shafiei, E. Milios (2012)
Finding expert users in community question answeringProceedings of the 21st International Conference on World Wide Web
José Pedro, Alexandros Karatzoglou (2014)
Question recommendation for collaborative question answering systems with RankSLDA
Abhishek Singh, N. Nagwani, S. Pandey (2018)
Efficient Management of Community Question Answering Sites using Improved Spectral Clustering
Xueqi Cheng, Xiaohui Yan, Yanyan Lan, Jiafeng Guo (2014)
BTM: Topic Modeling over Short TextsIEEE Transactions on Knowledge and Data Engineering, 26
Jinwen Guo, Shengliang Xu, Shenghua Bao, Yong Yu (2008)
Tapping on the potential of q&a community by recommending answer providers
S. Geman, D. Geman (1984)
Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of ImagesIEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-6
L. Cagnina, M. Errecalde, Diego Ingaramo, Paolo Rosso (2008)
A DISCRETE PARTICLE SWARM OPTIMIZER FOR CLUSTERING SHORT-TEXT CORPORA
A large number of questions are posted on community question answering (CQA) websites every day. Providing a set of core questions will ease the question overload problem. These core questions should cover the main content of the original question set. There should be low redundancy within the core questions and a consistent distribution with the original question set. The paper aims to discuss these issues.Design/methodology/approachIn the paper, a method named QueExt method for extracting core questions is proposed. First, questions are modeled using a biterm topic model. Then, these questions are clustered based on particle swarm optimization (PSO). With the clustering results, the number of core questions to be extracted from each cluster can be determined. Afterwards, the multi-objective PSO algorithm is proposed to extract the core questions. Both PSO algorithms are integrated with operators in genetic algorithms to avoid the local optimum.FindingsExtensive experiments on real data collected from the famous CQA website Zhihu have been conducted and the experimental results demonstrate the superior performance over other benchmark methods.Research limitations/implicationsThe proposed method provides new insight into and enriches research on information overload in CQA. It performs better than other methods in extracting core short text documents, and thus provides a better way to extract core data. The PSO is a novel method used for selecting core questions. The research on the application of the PSO model is expanded. The study also contributes to research on PSO-based clustering. With the integration of K-means++, the key parameter number of clusters is optimized.Originality/valueThe novel core question extraction method in CQA is proposed, which provides a novel and efficient way to alleviate the question overload. The PSO model is extended and novelty used in selecting core questions. The PSO model is integrated with K-means++ method to optimize the number of clusters, which is just the key parameter in text clustering based on PSO. It provides a new way to cluster texts.
Data Technologies and Applications – Emerald Publishing
Published: Oct 22, 2019
Keywords: Knowledge management; Social media; Particle swarm optimization; Text mining; Community question answering; Core question extraction
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.