Design Demand Trend Acquisition Method Based on Short Text Mining of User Comments in Shopping Websites
In order to facilitate designers to explore the market demand trend of laptops and to establish a better “network users-market feedback mechanism”, 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 clus...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2078-2489/13/3/110 |
| _version_ | 1797470690006269952 |
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| author | Zhiyong Xiong Zhaoxiong Yan Huanan Yao Shangsong Liang |
| author_facet | Zhiyong Xiong Zhaoxiong Yan Huanan Yao Shangsong Liang |
| author_sort | Zhiyong Xiong |
| collection | DOAJ |
| description | In order to facilitate designers to explore the market demand trend of laptops and to establish a better “network users-market feedback mechanism”, 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’s attention factors, score the emotional tendency, and analyze the user’s 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. |
| first_indexed | 2024-03-09T19:40:36Z |
| format | Article |
| id | doaj.art-96c70ff14c474306b1181511acc09d06 |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-03-09T19:40:36Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj.art-96c70ff14c474306b1181511acc09d062023-11-24T01:41:19ZengMDPI AGInformation2078-24892022-02-0113311010.3390/info13030110Design Demand Trend Acquisition Method Based on Short Text Mining of User Comments in Shopping WebsitesZhiyong Xiong0Zhaoxiong Yan1Huanan Yao2Shangsong Liang3School of Design, South China University of Technology, Guangzhou 510006, ChinaSchool of Design, South China University of Technology, Guangzhou 510006, ChinaGuangzhou Code Camp Technology Co., Ltd., Guangzhou 510000, ChinaDepartment of Machine Learning, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi 7909, United Arab EmiratesIn order to facilitate designers to explore the market demand trend of laptops and to establish a better “network users-market feedback mechanism”, 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’s attention factors, score the emotional tendency, and analyze the user’s 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.https://www.mdpi.com/2078-2489/13/3/110short text miningnetwork usersuser reviewemotional orientation matchingvisualization |
| spellingShingle | Zhiyong Xiong Zhaoxiong Yan Huanan Yao Shangsong Liang Design Demand Trend Acquisition Method Based on Short Text Mining of User Comments in Shopping Websites Information short text mining network users user review emotional orientation matching visualization |
| title | Design Demand Trend Acquisition Method Based on Short Text Mining of User Comments in Shopping Websites |
| title_full | Design Demand Trend Acquisition Method Based on Short Text Mining of User Comments in Shopping Websites |
| title_fullStr | Design Demand Trend Acquisition Method Based on Short Text Mining of User Comments in Shopping Websites |
| title_full_unstemmed | Design Demand Trend Acquisition Method Based on Short Text Mining of User Comments in Shopping Websites |
| title_short | Design Demand Trend Acquisition Method Based on Short Text Mining of User Comments in Shopping Websites |
| title_sort | design demand trend acquisition method based on short text mining of user comments in shopping websites |
| topic | short text mining network users user review emotional orientation matching visualization |
| url | https://www.mdpi.com/2078-2489/13/3/110 |
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