423
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Comparative relation mining of customer reviews based on a hybrid CSR method

, , , &
Article: 2251717 | Received 13 Nov 2022, Accepted 19 Aug 2023, Published online: 06 Oct 2023

References

  • Alhamzeh, A., Bouhaouel, M., Egyed-Zsigmond, E., & Mitrović, J. (2021). Distilbert-based argumentation retrieval for answering comparative questions. In Proceedings of the Conference and Labs of the Evaluation Forum (CLEF 2021), 2936 (pp. 209–212).
  • Anwar, T., & Uma, V. (2022). CD-SPM: Cross-domain book recommendation using sequential pattern mining and rule mining. Journal of King Saud University – Computer and Information Sciences, 34(3), 793–800. https://doi.org/10.1016/j.jksuci.2019.01.012
  • Beloucif, M., Yimam, S. M., Stahlhacke, S., & Biemann, C. (2022). Elvis vs. M. Jackson: Who has More albums? Classification and identification of elements in comparative questions. In Proceedings of the 13th International Conference on Language Resources and Evaluation (LREC), Marseille, France (pp. 3771–3779).
  • Bondarenko, A., Ajjour, Y., Dittmar, V., Homann, N., Braslavski, P., & Hagen, M. (2022). Towards understanding and answering comparative questions. In Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining (pp. 66–74). https://doi.org/10.1145/3488560.3498534.
  • Bondarenko, A., Braslavski, P., Volske, M., Aly, R., Frobe, M., Panchenko, A., Biemann, C., Stein, B., & Hagen, M. (2020). Comparative web search questions. Proceedings of the 13th International Conference on Web Search and Data Mining (WSDM '20). Association for Computing Machinery, New York, NY, USA, 52–60. https://doi.org/10.1145/3336191.3371848
  • Fei, H., Ren, Y., & Ji, D. (2020). Boundaries and edges rethinking: an end-to-end neural model for overlapping entity relation extraction. Information Processing & Management, 57(6), 102311. https://doi.org/10.1016/j.ipm.2020.102311
  • Gao, S., Tang, O., Wang, H., & Yin, P. (2018). Identifying competitors through comparative relation mining of online reviews in the restaurant industry. International Journal of Hospitality Management, 71, 19–32. https://doi.org/10.1016/j.ijhm.2017.09.004
  • Gao, S., Wang, H. W., Liu, J. Q., Zhu, Y. J., & Tang, O. (2023). Comparative relation mining of online reviews: A hierarchical multi-attention network model. International Journal of Mobile Communications, 22(2), 212–236. https://doi.org/10.1504/IJMC.2023.132572
  • Guo, Y., Wang, F., Xing, C., & Lu, X. (2022). Mining multi-brand characteristics from online reviews for competitive analysis: A brand joint model using latent Dirichlet allocation. Electronic Commerce Research and Applications, 53, 101141. https://doi.org/10.1016/j.elerap.2022.101141
  • Huang, X. J., Wan, X. J., & Yang, J. W. (2008). Learning to identify Chinese comparative sentences. Journal of Chinese Information Processing, 22(5), 30–38. In Chinese.
  • Iso, H., Wang, X., Angelidis, S., & Suhara, Y. (2021). Comparative opinion summarization via collaborative decoding. In Proceedings of the Association for Computational Linguistics, Dublin, Ireland (pp. 3307–3324). arXiv preprint arXiv:2110.07520.
  • Jain, P. K., Quamer, W., Pamula, R., & Saravanan, V. (2023). SpSAN: Sparse self-attentive network-based aspect-aware model for sentiment analysis. Journal of Ambient Intelligence and Humanized Computing, 14(4), 3091–3108. https://doi.org/10.1007/s12652-021-03436-x
  • Jain, P. K., Srivastava, G., Lin, J. C. W., & Pamula, R. (2022). Unscrambling customer recommendations: a novel LSTM ensemble approach in airline recommendation prediction using online reviews. IEEE Transactions on Computational Social Systems, 9(6), 1777–1784. https://doi.org/10.1109/TCSS.2022.3200890
  • Khan, A., Younis, U., Kundi, A. S., Asghar, M. Z., & Ahmed, I. (2020). Sentiment classification of user reviews using supervised learning techniques with comparative opinion mining perspective. In Proceedings of the 2019 Computer Vision Conference (CVC), 21 (pp. 23–29).
  • Kim, S. G., & Kang, J. M. (2018). Analyzing the discriminative attributes of products using text mining focused on cosmetic reviews. Information Processing & Management, 54(6), 938–957. https://doi.org/10.1016/j.ipm.2018.06.003
  • Liu, H., Yin, X., Song, S., Gao, S., & Zhang, M. (2022). Mining detailed information from the description for App functions comparison. IET Software, 16(1), 94–110. https://doi.org/10.1049/sfw2.12042
  • Liu, J., Wang, X., & Huang, L. (2021a). Fusing various document representations for comparative text identification from product reviews. In Proceedings of the International Conference on Web Information Systems and Applications (pp. 531–543).
  • Liu, Y., Jiang, C., & Zhao, H. (2019). Assessing product competitive advantages from the perspective of customers by mining user-generated content on social media. Decision Support Systems, 123, 113079. https://doi.org/10.1016/j.dss.2019.113079
  • Liu, Z., Qin, C. X., & Zhang, Y. J. (2021b). Mining product competitiveness by fusing multisource online information. Decision Support Systems, 143, 113477. https://doi.org/10.1016/j.dss.2020.113477
  • Liu, Z., Xia, R., & Yu, J. (2021c). Comparative opinion quintuple extraction from product reviews. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (pp. 3955–3965). https://doi.org/10.18653/v1/2021.emnlp-main.322.
  • Messaoudi, C., Guessoum, Z., & Ben Romdhane, L. (2022). Opinion mining in online social media: a survey. Social Network Analysis and Mining, 12(1), 25–32. https://doi.org/10.1007/s13278-021-00855-8
  • Noorian Avval, A.A., Harounabadi, A. (2023). A hybrid recommender system using topic modeling and prefixspan algorithm in social media. Complex & Intelligent Systems, 9, 4457–4482. https://doi.org/10.1007/s40747-022-00958-5
  • Ping, Q., & Chen, C. (2018). LitStoryTeller+: an interactive system for multi-level scientific paper visual storytelling with a supportive text mining toolbox. Scientometrics, 116(3), 1887–1944. https://doi.org/10.1007/s11192-018-2803-x
  • Sagnika, S., Mishra, B. S. P., & Meher, S. K. (2021). An attention-based CNN-LSTM model for subjectivity detection in opinion-mining. Neural Computing and Applications, 33(24), 17425–17438. https://doi.org/10.1007/s00521-021-06328-5
  • Serrano-Guerrero, J., Romero, F. P., & Olivas, J. A. (2021). Fuzzy logic applied to opinion mining: a review. Knowledge-Based Systems, 222, 107018. https://doi.org/10.1016/j.knosys.2021.107018
  • Subhashini, L. D. C. S., Li, Y., Zhang, J., Atukorale, A. S., & Wu, Y. (2021). Mining and classifying customer reviews: a survey. Artificial Intelligence Review, 54(8), 6343–6389. https://doi.org/10.1007/s10462-021-09955-5
  • Tkachenko, M., & Lauw, H. W. (2017). Comparative relation generative model. IEEE Transactions on Knowledge and Data Engineering, 29(4), 771–783. https://doi.org/10.1109/TKDE.2016.2640281
  • Vedula, N., Collins, M., Agichtein, E., & Rokhlenko, O. (2023). Generating explainable product comparisons for online shopping. In Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining (pp. 949–957). https://doi.org/10.1145/3539597.3570489.
  • Vo, D. T., Al-Obeidat, F., & Bagheri, E. (2020). Extracting temporal and causal relations based on event networks. Information Processing & Management, 57(6), 102319. https://doi.org/10.1016/j.ipm.2020.102319
  • Vo, D. T., & Bagheri, E. (2017). Self-training on refined clause patterns for relation extraction. Information Processing and Management, 54(4), 686–706.
  • Wang, H., Chen, C., Xing, Z., & Grundy, J. (2021). Difftech: Differencing similar technologies from crowd-scale comparison discussions. IEEE Transactions on Software Engineering, 48(7), 2399–2241. https://doi.org/10.1109/TSE.2021.3059885
  • Wang, H. W., Gao, S., Yin, P., & Liu, J. N. (2017a). Competitiveness analysis through comparative relation mining: evidence from restaurants’ online reviews. Industrial Management & Data Systems, 117(4), 672–687. https://doi.org/10.1108/IMDS-07-2016-0284
  • Wang, W., Xin, G., & Wang, B. (2017b). Sentiment information Extraction of comparative sentences based on CRF model. Computer Science and Information Systems, 14(3), 823–837. https://doi.org/10.2298/CSIS161229031W
  • Wei, N., Zhao, S., Liu, J., & Wang, S. (2022). A novel textual data augmentation method for identifying comparative text from user-generated content. Electronic Commerce Research and Applications, 53, 101143. https://doi.org/10.1016/j.elerap.2022.101143
  • Wei, N., Zhao, S., Liu, J., & Wang, S. (2023). A review for comparative text mining: From data acquisition to practical application. Journal of Information Science, published online. https://doi.org/10.1177/01655515231165228
  • Yang, S., Wei, R., Guo, J. Z., & Tan, H. L. (2020). Chinese semantic document classification based on strategies of semantic similarity computation and correlation analysis. Journal of Web Semantics, 63(8), 100578. doi:10.1016/j.websem.2020.100578