Abstract
In recent years, the recommendation system has become one of the important tools of e-commerce, which provides suggestions to the user for some resources such as hotels, songs, books, movies, etc. The existing hotel recommendation method has faced many problems such as data sparsity, cold-start problems, scalability, etc. Traditional Convolutional Neural Networks (CNNs) often struggle to capture long-term semantic characteristics, and their variants, such as Dilated CNNs, may encounter issues with gradient exploding. Moreover, Gated Recurrent Units (GRUs) and Bidirectional GRUs, while effective in capturing context information, may suffer from low learning efficiency and convergence challenges. Hence, this paper proposes the hotel recommendation system to use the hybrid of dilated multichannel convolutional neural network (MCNN) and bi-directional gated recurrent unit (BiGRU) with an attention mechanism. The main aim of this research is to develop a more efficient, scalable, regularized, and generalized recommendation system which can recommend the name of the hotels to the travellers based on their preferences by analysing the previous so far traveller’s comments together with the rating value to improve the forecast accuracy. The aspect based attention mechanisms are employed to evaluate the word, sentence, and semantic level similarity weight based vectors for mining useful information. The proposed approach has shown improved performance than existing approaches in terms of 99.46% Accuracy, 98.94% Precision, 98.84% Recall, and 98.75% F1-score.
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References
Ahmad W, Khan HU, Iqbal T, Iqbal S (2023) Attention-based multi-channel gated recurrent neural networks: a novel feature-centric approach for aspect-based sentiment classification. IEEE Access 2023:1
Ahmed K, Nadeem MI, Zheng Z, Li D, Ullah I, Assam M, Mohamed HG (2023) Breaking down linguistic complexities: a structured approach to aspect-based sentiment analysis. J King Saud Univ Comput Inf Sci 35(8):101651
Alam M, Abid F, Guangpei C, Yunrong LV (2020) Social media sentiment analysis through parallel dilated convolutional neural network for smart city applications. Comput Commun 154:129–137
Anandarajan M, Hill C, Nolan T (2019) Practical text analytics. Maximizing the value of text data (Advances in analytics and data science, vol 2). Springer, London, pp 45–59
Berrimi M, Oussalah M, Moussaoui A, Saidi M (2023) Attention mechanism architecture for Arabic sentiment analysis. ACM Trans Asian Low Resource Lang Inf Process 22(4):1–26
Cellary W, Mokbel MF, Wang J, Wang H, Zhou R, Zhang Y (eds) (2016) Web information systems engineering—WISE 2016: 17th international conference, Shanghai, China, November 8–10, 2016, proceedings, Part I, vol 10041. Springer, London
Chang SH, Abdul A, Chen J, Liao HY (2018, April) A personalized music recommendation system using convolutional neural networks approach. In: 2018 IEEE international conference on applied system invention (ICASI). IEEE, pp 47–49
Chang V, Liu L, Xu Q, Li T, Hsu CH (2023) An improved model for sentiment analysis on luxury hotel review. Expert Syst 40(2):e12580
Chen T (2020) A fuzzy ubiquitous traveler clustering and hotel recommendation system by differentiating travelers’ decision-making behaviors. Appl Soft Comput 96:106585
Chen T, Chuang YH (2018) Fuzzy and nonlinear programming approach for optimizing the performance of ubiquitous hotel recommendation. J Ambient Intell Humaniz Comput 9:275–284
Chen ZG, Kang HS, Yin SN, Kim SR (2016) An efficient privacy protection in mobility social network services with novel clustering-based anonymization. EURASIP J Wirel Commun Netw 2016:1–9
Cheng Y, Sun H, Chen H, Li M, Cai Y, Cai Z, Huang J (2021) Sentiment analysis using multi-head attention capsules with multi-channel CNN and bidirectional GRU. IEEE Access 9:60383–60395
Cheng Y, Yao L, Xiang G, Zhang G, Tang T, Zhong L (2020) Text sentiment orientation analysis based on multi-channel CNN and bidirectional GRU with attention mechanism. IEEE Access 8:134964–134975
Dey R, Salem FM (2017, August) Gate-variants of gated recurrent unit (GRU) neural networks. In: 2017 IEEE 60th international midwest symposium on circuits and systems (MWSCAS). IEEE, pp 1597–1600
Gan C, Feng Q, Zhang Z (2021) Scalable multi-channel dilated CNN–BiLSTM model with attention mechanism for Chinese textual sentiment analysis. Futur Gener Comput Syst 118:297–309
Gao S, Young MT, Qiu JX, Yoon HJ, Christian JB, Fearn PA, Ramanthan A (2018) Hierarchical attention networks for information extraction from cancer pathology reports. J Am Med Inform Assoc 25(3):321–330
Hossen MS, Jony AH, Tabassum T, Islam MT, Rahman MM, Khatun T (2021, March) Hotel review analysis for the prediction of business using deep learning approach. In: 2021 international conference on artificial intelligence and smart systems (ICAIS). IEEE, pp 1489–1494
Huming G, Weili L (2010, April) A hotel recommendation system based on collaborative filtering and rankboost algorithm. In: 2010 2nd international conference on multimedia and information technology, vol 1. IEEE, pp 317–320
Jalan K, Gawande K (2017, August) Context-aware hotel recommendation system based on hybrid approach to mitigate cold-start-problem. In: 2017 international conference on energy, communication, data analytics and soft computing (ICECDS). IEEE, pp 2364–2370
John A, Latha T (2023) Stock market prediction based on deep hybrid RNN model and sentiment analysis. Automatika 64(4):981–995
Kabir ME, Wang H, Bertino E (2011) Efficient systematic clustering method for k-anonymization. Acta Informatica 48:51–66
Kaya B (2020) A hotel recommendation system based on customer location: a link prediction approach. Multimed Tools Appl 79:1745–1758
Li J, Zhang Y, Ning J, Huang X, Poh GS, Wang D (2020) Attribute based encryption with privacy protection and accountability for CloudIoT. IEEE Trans Cloud Comput 10(2):762–773
Li W, Xu B (2020) Aspect-based fashion recommendation with attention mechanism. IEEE Access 8:141814–141823
Li Z, Sun Y, Zhu J, Tang S, Zhang C, Ma H (2021) Improve relation extraction with dual attention-guided graph convolutional networks. Neural Comput Appl 33:1773–1784
Lin KP, Lai CY, Chen PC, Hwang SY (2015, October) Personalized hotel recommendation using text mining and mobile browsing tracking. In: 2015 IEEE international conference on systems, man, and cybernetics. IEEE, pp 191–196
Liu G, Guo J (2019) Bidirectional LSTM with attention mechanism and convolutional layer for text classification. Neurocomputing 337:325–338
Liu J, Yang Y, Lv S, Wang J, Chen H (2019). Attention-based BiGRU–CNN for Chinese question classification. J Ambient Intell Human Comput 2019:1–12
Liu N, Shen B (2023) Aspect term extraction via information-augmented neural network. Compl Intell Syst 9(1):537–563
Majeed A, Lee S (2020) Anonymization techniques for privacy preserving data publishing: a comprehensive survey. IEEE Access 9:8512–8545
Muhammad PF, Kusumaningrum R, Wibowo A (2021) Sentiment analysis using Word2vec and long short-term memory (LSTM) for Indonesian hotel reviews. Proc Comput Sci 179:728–735
Nedjah N, Santos I, de Macedo Mourelle L (2022) Sentiment analysis using convolutional neural network via word embeddings. Evol Intel 15(4):2295–2319
Nilashi M, Ahani A, Esfahani MD, Yadegaridehkordi E, Samad S, Ibrahim O, Akbari E (2019) Preference learning for eco-friendly hotels recommendation: a multi-criteria collaborative filtering approach. J Cleaner Prod 215:767–783
Pandya S, Shah J, Joshi N, Ghayvat H, Mukhopadhyay SC, Yap MH (2016, November) A novel hybrid based recommendation system based on clustering and association mining. In: 2016 10th international conference on sensing technology (ICST). IEEE, pp 1–6
Rani MS, Subramanian S (2020) Attention mechanism with gated recurrent unit using convolutional neural network for aspect level opinion mining. Arab J Sci Eng 45:6157–6169
Ray B, Garain A, Sarkar R (2021) An ensemble-based hotel recommender system using sentiment analysis and aspect categorization of hotel reviews. Appl Soft Comput 98:106935
Shambour Q, Fraihat S (2016) An item-based multi-criteria collaborative filtering algorithm for personalized recommender systems. Int J Adv Comput Sci Appl 7(8):1
Sharma Y, Bhatt J, Magon R (2015, October) A multi-criteria review-based hotel recommendation system. In: 2015 IEEE international conference on computer and information technology; ubiquitous computing and communications; dependable, autonomic and secure computing; pervasive intelligence and computing. IEEE, pp 687–691
Sun X, Ding B (2022) Neural network with hierarchical attention mechanism for contextual topic dialogue generation. IEEE Access 10:4628–4639
Sweidan AH, El-Bendary N, Al-Feel H (2021) Sentence-level aspect-based sentiment analysis for classifying adverse drug reactions (ADRs) using hybrid ontology-XLNet transfer learning. IEEE Access 9:90828–90846
Takuma K, Yamamoto J, Kamei S, Fujita S (2016, November) A hotel recommendation system based on reviews: What do you attach importance to? In: 2016 4th international symposium on computing and networking (CANDAR). IEEE, pp 710–712
Verma S, Kumar A, Sharan A (2023) MuCon: Multi-channel convolution for targeted sentiment classification. Multimed Tools Appl 2023:1–19
Wang D, Su J, Yu H (2020) Feature extraction and analysis of natural language processing for deep learning English language. IEEE Access 8:46335–46345
Wei R, Tian H, Shen H (2018) Improving k-anonymity based privacy preservation for collaborative filtering. Comput Electr Eng 67:509–519
Wei Y, Ma H, Wang Y, Li Z, Chang L (2023) Dual graph attention networks for multi-behavior recommendation. Int J Mach Learn Cybern 14(8):2831–2846
Widaningrum I, Mustikasari D, Arifin R, Tsaqila SL, Fatmawati D (2022) Algoritma term frequency-inverse document frequency (TF-IDF) dan K-means clustering Untuk Menentukan Kategori Dokumen. Prosid Sisfotek 6(1):145–149
Yelisetti S, Geethanjali N (2023) Aspect-based text classification for sentimental analysis using attention mechanism with RU-BiLSTM. Scalable Comput Pract Exp 24(3):299–314
Zeng Y, Li Z, Chen Z, Ma H (2023) Aspect-level sentiment analysis based on semantic heterogeneous graph convolutional network. Front Comp Sci 17(6):176340
Zeng Y, Li Z, Tang Z, Chen Z, Ma H (2023) Heterogeneous graph convolution based on in-domain self-supervision for multimodal sentiment analysis. Expert Syst Appl 213:119240
Zhang C, & Gao J (2021, January) Hype-han: hyperbolic hierarchical attention network for semantic embedding. In: Proceedings of the 29th international conference on international joint conferences on artificial intelligence, pp 3990–3996
Zhang K, Wang K, Wang X, Jin C, Zhou A (2015, April) Hotel recommendation based on user preference analysis. In: 2015 31st IEEE international conference on data engineering workshops. IEEE, pp 134–138
Zhao G, Luo Y, Chen Q, Qian X (2023) Aspect-based sentiment analysis via multitask learning for online reviews. Knowl-Based Syst 264:110326
Zhou J, Chen Q, Huang JX, Hu QV, He L (2020) Position-aware hierarchical transfer model for aspect-level sentiment classification. Inf Sci 513:1–16
Zulqarnain M, Ghazali R, Aamir M, Hassim YMM (2024) An efficient two-state GRU based on feature attention mechanism for sentiment analysis. Multimed Tools Appl 83(1):3085–3110
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Jai Arul Jose, G., Mastan, M. & Al-Nuaimy, L.A.H. Aspect based hotel recommendation system using dilated multichannel CNN and BiGRU with hyperbolic linear unit. Int. J. Mach. Learn. & Cyber. (2024). https://doi.org/10.1007/s13042-024-02184-6
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DOI: https://doi.org/10.1007/s13042-024-02184-6