All Title Author
Keywords Abstract

Publish in OALib Journal
ISSN: 2333-9721
APC: Only $99

ViewsDownloads

Relative Articles

More...

基于UGC文本的动态多属性决策方法
Dynamic Multiple-Attribute Decision Making Method Based on UGC Text

DOI: 10.12677/HJDM.2023.131006, PP. 55-66

Keywords: UGC文本,多属性决策,动态决策模型,情感分析,UGC Text, Multi-Attribute Decision Making, Dynamic Decision Model, Sentiment Analysis

Full-Text   Cite this paper   Add to My Lib

Abstract:

网络中的大量UGC文本包含了用户对产品的真实评价,如何利用评论文本对产品进行决策或排序越来越受到重视。本文提出了基于UGC的动态多属性决策方法。首先,面对非结构化的文本信息难以直接被机器理解,提出了属性信息提取方法。从文本中提取用户关注的产品属性,基于情感分析方法对属性评价值进行计算,并结合属性频次和情感分歧度指标定义了属性权重计算方法。然后,考虑到UGC文本内容的动态变化导致不同时段的信息对当前决策的参考价值不同,本文在多属性决策框架的基础上提出了区分时间窗口的动态决策模型,时间窗口的划分基于属性相似性,同时结合时间距离给出了时间权重计算方法。最后,运用本文提出的方法结合VIKOR排序算法对基于游记的旅游目的地排序问题进行了实验求解,说明了本文方法的可行性和实用性。
A large number of UGC texts in the network contain users’ real evaluations of products. How to use the comment texts to make decisions or rank products has been paid more attention. This paper proposes a dynamic multi-attribute decision-making method based on UGC. First of all, in the face of unstructured text information that is difficult to be directly understood by the machine, an attribute information extraction method is proposed to extract the product attributes that users care about from the text, then calculate the attribute evaluation value based on the sentiment analysis method, and define the attribute weight combining the attribute frequency and sentiment divergence index. Secondly, considering that the dynamic changes of online review content will lead to different reference values of information in different periods for current decisions, this paper pro-poses a dynamic decision model to distinguish time windows based on the multi-attribute decision-making framework. The division of time windows is based on attribute similarity, and the calculation method of time weight is given in combination with time distance. Finally, the proposed method combined with the VIKOR sorting algorithm is used to solve the tourism destination sorting problem based on travel notes, which shows the feasibility and practicability of the proposed method.

References

[1]  Gou, X., Xu, Z. and Herrera, F. (2018) Consensus Reaching Process for Large-Scale Group Decision Making with Double Hierarchy Hesitant Fuzzy Linguistic Preference Relations. Knowledge-Based Systems, 157, 20-33.
https://doi.org/10.1016/j.knosys.2018.05.008
[2]  Dong, Y., Zhao, S., Zhang, H., et al. (2018) A Self-Management Mechanism for Noncooperative Behaviors in Large- Scale Group Consensus Reaching Processes. IEEE Transactions on Fuzzy Systems, 26, 3276-3288.
https://doi.org/10.1109/TFUZZ.2018.2818078
[3]  Li, C.-C., Dong, Y. and Herrera, F. (2018) A Consensus Model for Large-Scale Linguistic Group Decision Making with a Feedback Recommendation Based on Clustered Per-sonalized Individual Semantics and Opposing Consensus Groups. IEEE Transactions on Fuzzy Systems, 27, 221-233.
https://doi.org/10.1109/TFUZZ.2018.2857720
[4]  Nguyen, H., Calantone, R. and Krishnan, R. (2020) Influence of Social Media Emotional Word of Mouth on Institutional Investors’ Decisions and Firm Value. Management Science, 66, 887-910.
https://doi.org/10.1287/mnsc.2018.3226
[5]  Chang, Y.-C., Ku, C.-H. and Chen, C.-H. (2019) Social Media Ana-lytics: Extracting and Visualizing Hilton Hotel Ratings and Reviews from Trip Advisor. International Journal of Infor-mation Management, 48, 263-279.
https://doi.org/10.1016/j.ijinfomgt.2017.11.001
[6]  Xu, X., Yin, X. and Chen, X. (2019) A Large-Group Emer-gency Risk Decision Method Based on Data Mining of Public Attribute Preferences. Knowledge-Based Systems, 163, 495-509.
https://doi.org/10.1016/j.knosys.2018.09.010
[7]  张瑾, 尤天慧, 樊治平. 基于多属性在线评价信息的商品购买推荐排序方法[J]. 东北大学学报(自然科学版), 2019, 40(1): 138-143.
[8]  由丽萍, 王嘉敏. 基于情感分析和VIKOR多属性决策法的电子商务顾客满意感测度[J]. 情报学报, 2015, 34(10): 1098-1110.
[9]  尤天慧, 张瑾, 樊治平. 基于情感分析和证据理论的多属性在线评论决策方法[J]. 系统管理学报, 2019, 28(3): 536-544.
[10]  李永海. 一种使用在线评论信息的商品购买决策分析方法[J]. 运筹与管理, 2018, 27(2): 32-37.
[11]  Kang, D. and Park, Y. (2014) Based Measurement of Customer Satisfaction in Mobile Service: Sentiment Analysis and VIKOR Approach. Expert Systems with Applications, 41, 1041-1050.
https://doi.org/10.1016/j.eswa.2013.07.101
[12]  汪兰林, 李登峰. 基于在线评价信息的概率语言多属性变权决策方法[J]. 运筹与管理, 2021, 30(2): 39-44.
[13]  Peng, Y., Kou, G. and Li, J. (2014) A Fuzzy PROMETHEE Ap-proach for Mining Customer Reviews in Chinese. Arabian Journal for Science and Engineering, 39, 5245-5252.
https://doi.org/10.1007/s13369-014-1033-7
[14]  贾凡. 不确定信息环境下多准则群决策方法研究[D]: [博士学位论文]. 济南: 山东大学, 2017.
[15]  Blei, D.M., et al. (2003) Latent Dirichlet Allocation. Journal of Machine Learn-ing Research, 3, 993-1022.
[16]  顾畑甜. 基于游记的旅游意图的挖掘方法[D]: [硕士学位论文]. 上海: 东华大学, 2021.
[17]  宋晓雷, 王素格, 李红霞. 面向特定领域的产品评价对象自动识别研究[J]. 中文信息学报, 2010, 24(1): 89-93.
[18]  徐泽水. 基于相离度和可能度的偏差最大化多属性决策方法[J]. 控制与决策, 2001, 16(z1): 818-821.
[19]  刘德海. 基于最大偏差原则的群体性事件应急管理绩效评价模型[J]. 中国管理科学, 2016, 24(4): 138-147.
[20]  Tang, E.K., Suganthan, P.N. and Yao, X. (2006) An Analysis of Diversity Measures. Machine Learning, 65, 247-271.
https://doi.org/10.1007/s10994-006-9449-2
[21]  Ebbinghaus, H. (2013) Memory: A Contribution to Experimental Psychology. Annals of Neurosciences, 20, 155.
https://doi.org/10.5214/ans.0972.7531.200408

Full-Text

comments powered by Disqus

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133

WeChat 1538708413