{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T20:37:02Z","timestamp":1778877422986,"version":"3.51.4"},"reference-count":60,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,2,25]],"date-time":"2022-02-25T00:00:00Z","timestamp":1645747200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51105145"],"award-info":[{"award-number":["51105145"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>In order to facilitate designers to explore the market demand trend of laptops and to establish a better \u201cnetwork users-market feedback mechanism\u201d, we propose a design and research method of a short text mining tool based on the K-means clustering algorithm and Kano mode. An improved short text clustering algorithm is used to extract the design elements of laptops. Based on the traditional questionnaire, we extract the user\u2019s attention factors, score the emotional tendency, and analyze the user\u2019s needs based on the Kano model. Then, we select 10 laptops, process them by the improved algorithm, cluster the evaluation words and quantify the emotional orientation matching. Based on the obtained data, we design a visual interaction logic and usability test. These prove that the proposed method is feasible and effective.<\/jats:p>","DOI":"10.3390\/info13030110","type":"journal-article","created":{"date-parts":[[2022,2,25]],"date-time":"2022-02-25T10:00:40Z","timestamp":1645783240000},"page":"110","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Design Demand Trend Acquisition Method Based on Short Text Mining of User Comments in Shopping Websites"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0213-9973","authenticated-orcid":false,"given":"Zhiyong","family":"Xiong","sequence":"first","affiliation":[{"name":"School of Design, South China University of Technology, Guangzhou 510006, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhaoxiong","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Design, South China University of Technology, Guangzhou 510006, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huanan","family":"Yao","sequence":"additional","affiliation":[{"name":"Guangzhou Code Camp Technology Co., Ltd., Guangzhou 510000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shangsong","family":"Liang","sequence":"additional","affiliation":[{"name":"Department of Machine Learning, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi 7909, United Arab Emirates"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Hirsch, S., Novgorodov, S., Guy, I., and Nus, A. (2021, January 8\u201312). Generating Tips from Product Reviews. Proceedings of the 14th ACM International Conference on Web Search and Data Mining, New York, NY, USA.","DOI":"10.1145\/3437963.3441755"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"3528","DOI":"10.3390\/ijerph8093528","article-title":"Online Social Networking and Addiction-A Review of the Psychological Literature","volume":"8","author":"Daria","year":"2011","journal-title":"Int. J. Environ. Res. Public Health"},{"key":"ref_3","first-page":"65","article-title":"Web Analytics, Legal Framework and Estimation of Profitability of the Theater Website","volume":"2824","author":"Mochurad","year":"2021","journal-title":"CEUR Workshop Proc."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.eswa.2020.113465","article-title":"A deceptive review detection framework: Combination of coarse and fine-grained features","volume":"156","author":"Cao","year":"2020","journal-title":"Expert Syst. Appl."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"61756","DOI":"10.1109\/ACCESS.2021.3073657","article-title":"Using Artificial Intelligence to Understand What Causes Sentiment Changes on Social Media","volume":"9","author":"Alattar","year":"2021","journal-title":"IEEE Access"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"9375","DOI":"10.1007\/s12652-020-02654-z","article-title":"Extensive hotel reviews classification using long short term memory","volume":"12","author":"Ishaq","year":"2020","journal-title":"J. Ambient. Intell. Humaniz. Comput."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Ali, F., El-Sappagh, S., and Kwak, D. (2019). Fuzzy Ontology and LSTM-Based Text Mining: A Transportation Network Monitoring System for Assisting Travel. Sensors, 19.","DOI":"10.3390\/s19020234"},{"key":"ref_8","first-page":"e5765","article-title":"Short text similarity measurement using context-aware weighted biterms","volume":"15","author":"Yang","year":"2020","journal-title":"Neurocomputing"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"32215","DOI":"10.1109\/ACCESS.2020.2973430","article-title":"BTM and GloVe Similarity Linear Fusion-Based Short Text Clustering Algorithm for Microblog Hot Topic Discovery","volume":"8","author":"Wu","year":"2020","journal-title":"IEEE Access"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2384","DOI":"10.1007\/s10489-020-01672-w","article-title":"Targeted aspects oriented topic modeling for short texts","volume":"50","author":"He","year":"2020","journal-title":"Appl. Intell."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Selvaraj, S., and Choi, E. (2021). Swarm Intelligence Algorithms in Text Document Clustering with Various Benchmarks. Sensors, 21.","DOI":"10.3390\/s21093196"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Baccouche, A., Ahmed, S., Sierra-Sosa, D., and Elmaghraby, A. (2020). Malicious Text Identification: Deep Learning from Public Comments and Emails. Information, 11.","DOI":"10.3390\/info11060312"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"544","DOI":"10.1136\/amiajnl-2011-000464","article-title":"Natural language processing: An introduction","volume":"18","author":"Nadkarni","year":"2011","journal-title":"J. Am. Med. Inform. Assoc. Jamia"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1600","DOI":"10.1093\/jamia\/ocaa056","article-title":"The Unified Medical Language System SPECIALIST Lexicon and Lexical Tools: Development and applications","volume":"27","author":"Lu","year":"2020","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Cheng, X., Kong, X., Liao, L., and Li, B. (2020, January 8\u201312). A Combined Method for Usage of NLP Libraries Towards Analyzing Software Documents. Proceedings of the International Conference on Advanced Information Systems Engineering, Grenoble, France.","DOI":"10.1007\/978-3-030-49435-3_32"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1609","DOI":"10.1007\/s10489-019-01606-1","article-title":"A Dirichlet process biterm-based mixture model for short text stream clustering","volume":"50","author":"Chen","year":"2020","journal-title":"Appl. Intell."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3409585","article-title":"How Mobile App Design Overhauls Can Be Disastrous in Terms of User Perception: The Case of Snapchat","volume":"3","author":"Franzmann","year":"2020","journal-title":"ACM Trans. Soc. Comput."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"102034","DOI":"10.1016\/j.ipm.2019.04.002","article-title":"An evaluation of document clustering and topic modelling in two online social networks: Twitter and Reddit","volume":"57","author":"Curiskis","year":"2019","journal-title":"Inf. Process. Manag."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.is.2020.101662","article-title":"Topical affinity in short text microblogs","volume":"96","author":"Wandabwa","year":"2021","journal-title":"Inf. Syst."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2095","DOI":"10.1007\/s11063-021-10423-y","article-title":"User\u2019s Review Habits Enhanced Hierarchical Neural Network for Document-Level Sentiment Classification","volume":"53","author":"Chen","year":"2021","journal-title":"Neural Process. Lett."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.csl.2021.101196","article-title":"An Intention Multiple-representation Model with Expanded Information","volume":"68","author":"Hu","year":"2021","journal-title":"Comput. Speech Lang."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Abdulateef, S., Khan, N.A., Chen, B., and Shang, X. (2020). Multidocument Arabic Text Summarization Based on Clustering and Word2Vec to Reduce Redundancy. Information, 11.","DOI":"10.3390\/info11020059"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"114231","DOI":"10.1016\/j.eswa.2020.114231","article-title":"A new topic modeling based approach for aspect extraction in aspect based sentiment analysis: SS-LDA","volume":"168","author":"Ozyurt","year":"2020","journal-title":"Expert Syst. Appl."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2865","DOI":"10.1007\/s13369-019-04191-0","article-title":"A Novel Short Text Clustering Model Based on Grey System Theory","volume":"45","author":"Fidan","year":"2020","journal-title":"Arab. J. Sci. Eng."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"544","DOI":"10.1177\/0165551519849516","article-title":"ASA: A framework for Arabic sentiment Analysis","volume":"46","author":"Oussous","year":"2020","journal-title":"J. Inf. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"De Oliveira J\u00fanior, G.A., de Oliveira Albuquerque, R., Borges de Andrade, C.A., de Sousa, R.T., Sandoval Orozco, A.L., and Garc\u00eda Villalba, L.J. (2020). Anonymous Real-Time Analytics Monitoring Solution for Decision Making Supported by Sentiment Analysis. Sensors, 20.","DOI":"10.3390\/s20164557"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"654","DOI":"10.1016\/j.neucom.2016.06.045","article-title":"Data mining techniques in social media: A survey","volume":"214","author":"Injadat","year":"2016","journal-title":"Neurocomputing"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.patrec.2017.03.008","article-title":"K-means clustering with outlier removal","volume":"90","author":"Gan","year":"2017","journal-title":"Pattern Recognit. Lett."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1016\/j.jbi.2012.10.007","article-title":"Biomedical text mining and its applications in cancer research","volume":"46","author":"Zhu","year":"2013","journal-title":"J. Biomed. Inform."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"MacCuish, J.D., and MacCuish, N.E. (2010). Clustering in Bioinformatics and Drug Discovery, CRC Press.","DOI":"10.1201\/b10331"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1016\/j.patrec.2009.09.011","article-title":"Data clustering: 50 years beyond K-means","volume":"31","author":"Jain","year":"2010","journal-title":"Pattern Recognit. Lett."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"747","DOI":"10.1016\/j.asoc.2017.08.032","article-title":"Two improved k-means algorithms","volume":"68","author":"Yu","year":"2018","journal-title":"Appl. Soft Comput."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1109\/TKDE.2010.211","article-title":"Effective pattern discovery for text mining","volume":"24","author":"Zhong","year":"2010","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"142674","DOI":"10.1016\/j.scitotenv.2020.142674","article-title":"Attitude of Chinese public towards municipal solid waste sorting policy: A text mining study","volume":"756","author":"Wu","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"102060","DOI":"10.1016\/j.ipm.2019.102060","article-title":"Fuzzy topic modeling approach for text mining over short text","volume":"56","author":"Rashid","year":"2019","journal-title":"Inf. Process. Manag."},{"key":"ref_36","first-page":"3327","article-title":"On-line data retrieval algorithm with restart strategy in wireless networks","volume":"9","author":"He","year":"2014","journal-title":"J. Netw."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"3341","DOI":"10.1016\/j.jbusres.2016.02.010","article-title":"Predicting social media performance metrics and evaluation of the impact on brand building: A data mining approach","volume":"69","author":"Moro","year":"2016","journal-title":"J. Bus. Res."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"071402","DOI":"10.1115\/1.4030049","article-title":"Automated discovery of lead users and latent product features by mining large scale social media networks","volume":"137","author":"Tuarob","year":"2015","journal-title":"J. Mech. Des."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"726","DOI":"10.1016\/j.procs.2020.02.171","article-title":"Automatic short answer grading and feedback using text mining methods","volume":"169","author":"Gorban","year":"2020","journal-title":"Procedia Comput. Sci."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2444","DOI":"10.1016\/j.neucom.2017.11.019","article-title":"Corpus-based topic diffusion for short text clustering","volume":"275","author":"Zheng","year":"2018","journal-title":"Neurocomputing"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"101934","DOI":"10.1016\/j.ijinfomgt.2019.04.007","article-title":"Emotional Text Mining: Customer profiling in brand management","volume":"51","author":"Greco","year":"2020","journal-title":"Int. J. Inf. Manag."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"2171","DOI":"10.1093\/icesjms\/fsaa147","article-title":"Marine recreational fisheries\u2014Current state and future Opportunities","volume":"77","author":"Hyder","year":"2020","journal-title":"ICES J. Mar. Sci."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"5083213","DOI":"10.1155\/2016\/5083213","article-title":"Consumers\u2019 Kansei needs clustering method for product emotional design based on numerical design structure matrix and genetic algorithms","volume":"2016","author":"Yang","year":"2016","journal-title":"Comput. Intell. Neurosci."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"642","DOI":"10.1080\/09537325.2016.1220517","article-title":"Automated feature extraction from social media for systematic lead user identification","volume":"29","author":"Pajo","year":"2017","journal-title":"Technol. Anal. Strateg. Manag."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"12541","DOI":"10.1007\/s11042-020-10306-9","article-title":"A proposed UML-based common model for information visualization systems","volume":"80","author":"Moral","year":"2021","journal-title":"Multimed. Tools Appl."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Anne Parlina, K.R., and Murf, H. (2020). Theme Mapping and Bibliometrics Analysis of One Decade of Big Data Research in the Scopus Database. Information, 11.","DOI":"10.3390\/info11020069"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"684","DOI":"10.1016\/j.neucom.2016.05.053","article-title":"Multi-scale object retrieval via learning on graph from multimodal data","volume":"207","author":"Zhang","year":"2016","journal-title":"Neurocomputing"},{"key":"ref_48","unstructured":"Layton, R. (2015). Learning Data Mining with Python, Packt Publishing Ltd."},{"key":"ref_49","unstructured":"Raschka, S., and Mirjalili, V. (2017). Python Machine Learning: Machine Learning and Deep Learning with Python. Scikit-Learn, and TensorFlow, Packt. [2nd ed.]."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1016\/j.sbspro.2013.02.046","article-title":"Atomic data mining numerical methods, source code SQlite with Python","volume":"73","author":"Khwaldeh","year":"2013","journal-title":"Procedia-Soc. Behav. Sci."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Stan\u010din, I., and Jovi\u0107, A. (2019, January 20\u201324). An overview and comparison of free Python libraries for data mining and big data analysis. Proceedings of the 2019 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), Opatija, Croatia.","DOI":"10.23919\/MIPRO.2019.8757088"},{"key":"ref_52","first-page":"76","article-title":"Analysis of the Application of Python in Big Data Mining and Analysis","volume":"24","author":"Nie","year":"2018","journal-title":"J. Guangxi Univ. Natl."},{"key":"ref_53","unstructured":"Kane, F. (2017). Hands-on Data Science and Python Machine Learning, Packt Publishing Ltd."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.aci.2017.05.002","article-title":"A self-adaptive k-means classifier for business incentive in a fashion design environment","volume":"14","author":"Vincent","year":"2018","journal-title":"Appl. Comput. Inform."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"76","DOI":"10.4018\/IJISSS.2020040106","article-title":"Mining Keywords from Short Text Based on LDA-Based Hierarchical Semantic Graph Model","volume":"12","author":"Chen","year":"2020","journal-title":"Int. J. Inf. Syst. Serv. Sect. (IJISSS)"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"2066","DOI":"10.1007\/s11036-021-01742-4","article-title":"On exploiting Data Visualization and IoT for Increasing Sustainability and Safety in a Smart Campus","volume":"26","author":"Ceccarini","year":"2021","journal-title":"Mob. Netw. Appl."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/2945.981847","article-title":"Information visualization and visual data mining","volume":"8","author":"Keim","year":"2002","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"13","DOI":"10.2478\/aicue-2013-0002","article-title":"Using geographical information systems as an information visualization tool. A case study","volume":"60","year":"2013","journal-title":"Ann. Alexandru Ioan Cuza Univ.-Econ."},{"key":"ref_59","first-page":"149","article-title":"Emotional classification and visualization of movies based on their IMDb reviews","volume":"45","author":"Topal","year":"2017","journal-title":"Inf. Discov. Deliv."},{"key":"ref_60","first-page":"153","article-title":"Semiology of Graphics: Diagrams Networks Maps","volume":"48","author":"Kraak","year":"2011","journal-title":"Cartogr. J."}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/13\/3\/110\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:27:07Z","timestamp":1760135227000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/13\/3\/110"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,25]]},"references-count":60,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2022,3]]}},"alternative-id":["info13030110"],"URL":"https:\/\/doi.org\/10.3390\/info13030110","relation":{},"ISSN":["2078-2489"],"issn-type":[{"value":"2078-2489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,25]]}}}