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Erschienen in: Neural Computing and Applications 10/2021

27.08.2020 | S.I. : Higher Level Artificial Neural Network Based Intelligent Systems

A combined deep learning method for internet car evaluation

verfasst von: Deming Li, Menggang Li, Gang Han, Ting Li

Erschienen in: Neural Computing and Applications | Ausgabe 10/2021

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Abstract

In recent years, the Internet has become a trend in the development of the global automotive industry. Numerous Internet companies have joined the automobile manufacturing industry. At the same time, people generally search for information about cars on the Internet as an important reference to purchase decisions before buying them. As a high-value commodity, almost all consumers use search engines to find out the price, reputation and other information about their favorite models before they buy. On the other hand, online reviews contain a large amount of information about what consumers are saying about products, and they influence the purchasing decisions of potential consumers. It is observed that current reviews of automobiles can include several dimensions: corporate brand attention, corporate development and user reputation. In order to provide reference for users and car manufacturers, this paper established a systematic model of Internet car evaluation system based on topic feature extraction, the long short-term memory (LSTM) and the deep convolutional generative adversarial networks (DCGAN). Firstly, the model uses feature extraction and LSTM for sentiment analysis of user evaluations; secondly, considering anomalies in the sample processing, which makes it difficult to cover the distribution of the entire review sample, we proposed a way to train without using too many anomalous samples using DCGAN. The results show that this method can achieve an effective systematic evaluation of Internet cars using only a large sample of normal review events. The results can be used as a reference for people to buy a car and for car companies to optimize their products.

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Literatur
1.
Zurück zum Zitat Gong D, Tang M, Liu S, Xue G, Wang L (2019) Achieving sustainable transport through resource scheduling: a case study for electric vehicle charging stations. Adv Prod Eng Manag 14(1):65–79 Gong D, Tang M, Liu S, Xue G, Wang L (2019) Achieving sustainable transport through resource scheduling: a case study for electric vehicle charging stations. Adv Prod Eng Manag 14(1):65–79
2.
Zurück zum Zitat Zhang D, Sui J, Gong Y (2017) Large scale software test data generation based on collective constraint and weighted combination method. Tehnicki vjesnik/Tech Gaz 24(4):1041–1049 Zhang D, Sui J, Gong Y (2017) Large scale software test data generation based on collective constraint and weighted combination method. Tehnicki vjesnik/Tech Gaz 24(4):1041–1049
3.
Zurück zum Zitat Du J, Li Q, Qiao F, Yu L (2018) Estimation of vehicle emission on mainline freeway under isolated and integrated ramp metering strategies. Environ Eng Manag J 17(5):1237–1248CrossRef Du J, Li Q, Qiao F, Yu L (2018) Estimation of vehicle emission on mainline freeway under isolated and integrated ramp metering strategies. Environ Eng Manag J 17(5):1237–1248CrossRef
4.
Zurück zum Zitat Li LY (2018) Analysis of car brand opinion based on consumer reviews. Beijing University of Technology, Beijing Li LY (2018) Analysis of car brand opinion based on consumer reviews. Beijing University of Technology, Beijing
5.
Zurück zum Zitat Xu W, Yin Y (2018) Functional objectives decisionmaking of discrete manufacturing system based on integrated ant colony optimization and particle swarm optimization approach. Adv Prod Eng Manag 13(4):389 Xu W, Yin Y (2018) Functional objectives decisionmaking of discrete manufacturing system based on integrated ant colony optimization and particle swarm optimization approach. Adv Prod Eng Manag 13(4):389
6.
Zurück zum Zitat Liu S, Li F, Li F, Cheng X, Shen H (2013) Adaptive co-training SVM for sentiment classification on tweets. In: Proceedings of the 22nd ACM international conference on conference on information and knowledge management. ACM Liu S, Li F, Li F, Cheng X, Shen H (2013) Adaptive co-training SVM for sentiment classification on tweets. In: Proceedings of the 22nd ACM international conference on conference on information and knowledge management. ACM
7.
Zurück zum Zitat Lin J (2016) Research on the construction of data mining model of user online comments under the situation of social information situation–taking the construction of the negative opinion extracting system of auto-mobile industry as an example. Information ence Lin J (2016) Research on the construction of data mining model of user online comments under the situation of social information situation–taking the construction of the negative opinion extracting system of auto-mobile industry as an example. Information ence
8.
Zurück zum Zitat Gerhardt N, Schwolow S, Rohn S, Pérez-Cacho PR, Galán-Soldevilla H, Arce L, Weller P (2019) Corrigendum to Quality assessment of olive oils based on temperature-ramped HS–GC–IMS and sensory evaluation: comparison of different processing approaches by LDA, kNN, and SVM. Food Chem 286:307CrossRef Gerhardt N, Schwolow S, Rohn S, Pérez-Cacho PR, Galán-Soldevilla H, Arce L, Weller P (2019) Corrigendum to Quality assessment of olive oils based on temperature-ramped HS–GC–IMS and sensory evaluation: comparison of different processing approaches by LDA, kNN, and SVM. Food Chem 286:307CrossRef
9.
Zurück zum Zitat Gyamfi KS, Brusey J, Hunt A, Gaura E (2019) A dynamic linear model for heteroscedastic LDA under class imbalance. Neurocomputing 343:65–75CrossRef Gyamfi KS, Brusey J, Hunt A, Gaura E (2019) A dynamic linear model for heteroscedastic LDA under class imbalance. Neurocomputing 343:65–75CrossRef
10.
Zurück zum Zitat Tai KS, Socher R, Manning CD (2015) Improved semantic representations from tree-structured long short-term memory networks. arXiv preprint arXiv:1503.00075 Tai KS, Socher R, Manning CD (2015) Improved semantic representations from tree-structured long short-term memory networks. arXiv preprint arXiv:​1503.​00075
11.
Zurück zum Zitat Kaya M, Fidan G, Toroslu IH (2013) Transfer learning using Twitter data for improving sentiment classification of Turkish political news. Information sciences and systems 2013. Springer, Cham, pp 139–148CrossRef Kaya M, Fidan G, Toroslu IH (2013) Transfer learning using Twitter data for improving sentiment classification of Turkish political news. Information sciences and systems 2013. Springer, Cham, pp 139–148CrossRef
12.
Zurück zum Zitat Mnih V, Heess N, Graves A (2014) Recurrent models of visual attention. In: Advances in neural information processing systems, pp 2204–2212 Mnih V, Heess N, Graves A (2014) Recurrent models of visual attention. In: Advances in neural information processing systems, pp 2204–2212
13.
Zurück zum Zitat Bai X (2011) Predicting consumer sentiments from online text. Decis Support Syst 50(4):732–742CrossRef Bai X (2011) Predicting consumer sentiments from online text. Decis Support Syst 50(4):732–742CrossRef
14.
Zurück zum Zitat Li HY, Xu W, Cui Y, Wang Z, Xiao M, Sun ZX (2019) Preventive maintenance decision model of urban transportation system equipment based on multi-control units. IEEE Access 8:15851–15869CrossRef Li HY, Xu W, Cui Y, Wang Z, Xiao M, Sun ZX (2019) Preventive maintenance decision model of urban transportation system equipment based on multi-control units. IEEE Access 8:15851–15869CrossRef
15.
Zurück zum Zitat Meral M, Diri B (2014) Sentiment analysis on Twitter. In: Signal processing and communications applications conference. IEEE1 Meral M, Diri B (2014) Sentiment analysis on Twitter. In: Signal processing and communications applications conference. IEEE1
16.
Zurück zum Zitat He Y, Zhou D (2011) Self-training from labeled features for sentiment analysis. Inf Process Manag 47(4):606–616CrossRef He Y, Zhou D (2011) Self-training from labeled features for sentiment analysis. Inf Process Manag 47(4):606–616CrossRef
17.
Zurück zum Zitat MartíN-Valdivia MT, MartíNez-CáMara E, Perea-Ortega JM, UreñA-LóPez LA (2013) Sentiment polarity detection in Spanish reviews combining supervised and unsupervised approaches. Expert Syst Appl 40(10):3934–3942CrossRef MartíN-Valdivia MT, MartíNez-CáMara E, Perea-Ortega JM, UreñA-LóPez LA (2013) Sentiment polarity detection in Spanish reviews combining supervised and unsupervised approaches. Expert Syst Appl 40(10):3934–3942CrossRef
18.
Zurück zum Zitat Afify HM, Mohammed Kamel K, Hassanien AE (2020) Multi-images recognition of breast cancer histopathological via probabilistic neural network approach. 10:53 Afify HM, Mohammed Kamel K, Hassanien AE (2020) Multi-images recognition of breast cancer histopathological via probabilistic neural network approach. 10:53
19.
Zurück zum Zitat Bengio Y, Delalleau O (2011) On the expressive power of deep architectures. In: Discovery science-international conference Bengio Y, Delalleau O (2011) On the expressive power of deep architectures. In: Discovery science-international conference
20.
Zurück zum Zitat Wei RG, Zheng J, Zhang H, Zhang P et al (2017) A text emotion mining study on the introduction of marketing effects. Stat Decis Mak 09:50–55 Wei RG, Zheng J, Zhang H, Zhang P et al (2017) A text emotion mining study on the introduction of marketing effects. Stat Decis Mak 09:50–55
21.
Zurück zum Zitat Pang B, Lee L (2004) A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts. arXiv preprint arXiv: cs/0409058 Pang B, Lee L (2004) A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts. arXiv preprint arXiv:​ cs/​0409058
22.
Zurück zum Zitat Yang Z, Yang D, Dyer C, He X, Smola A, Hovy E (2016) Hierarchical attention networks for document classification. In: Proceedings of the 2016 conference of the North American chapter of the association for computational linguistics: human language technologies, pp 1480–1489 Yang Z, Yang D, Dyer C, He X, Smola A, Hovy E (2016) Hierarchical attention networks for document classification. In: Proceedings of the 2016 conference of the North American chapter of the association for computational linguistics: human language technologies, pp 1480–1489
23.
Zurück zum Zitat Zhou X, Wan X, Xiao J (2016) Attention-based LSTM network for cross-lingual sentiment classification. In: Proceedings of the 2016 conference on empirical methods in natural language processing, pp 247–256 Zhou X, Wan X, Xiao J (2016) Attention-based LSTM network for cross-lingual sentiment classification. In: Proceedings of the 2016 conference on empirical methods in natural language processing, pp 247–256
24.
Zurück zum Zitat Hu H, Wu Q, Zhang Z, Han S (2019) Effect of the manufacturer quality inspection policy on the supply chain decision-making and profits. Adv Prod Eng Manag 14(4):472–482 Hu H, Wu Q, Zhang Z, Han S (2019) Effect of the manufacturer quality inspection policy on the supply chain decision-making and profits. Adv Prod Eng Manag 14(4):472–482
25.
Zurück zum Zitat Feng Z, Zhang Z, Zhang Q, Gongab D (2018) Evaluation of soil suitability for cultivation based on back-propagation artificial neural network: the case of Jiangxia distrct. Environ Eng Manag J 17(1):229–235CrossRef Feng Z, Zhang Z, Zhang Q, Gongab D (2018) Evaluation of soil suitability for cultivation based on back-propagation artificial neural network: the case of Jiangxia distrct. Environ Eng Manag J 17(1):229–235CrossRef
26.
Zurück zum Zitat Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural Comput 9(8):1735–1780CrossRef Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural Comput 9(8):1735–1780CrossRef
27.
Zurück zum Zitat Kang H, Yoo SJ, Han D (2012) Senti-lexicon and improved Naïve Bayes algorithms for sentiment analysis of restaurant reviews. Expert Syst Appl 39(5):6000–6010CrossRef Kang H, Yoo SJ, Han D (2012) Senti-lexicon and improved Naïve Bayes algorithms for sentiment analysis of restaurant reviews. Expert Syst Appl 39(5):6000–6010CrossRef
28.
Zurück zum Zitat Wang X, Liu Y, Sun CJ, Wang B, Wang X (2015) Predicting polarities of tweets by composing word embeddings with long short-term memory. In: Proceedings of the 53rd annual meeting of the association for computational linguistics and the 7th international joint conference on natural language processing, vol 1, Long Papers, pp 1343–1353 Wang X, Liu Y, Sun CJ, Wang B, Wang X (2015) Predicting polarities of tweets by composing word embeddings with long short-term memory. In: Proceedings of the 53rd annual meeting of the association for computational linguistics and the 7th international joint conference on natural language processing, vol 1, Long Papers, pp 1343–1353
29.
Zurück zum Zitat Zhao PX, Gao WQ, Han X, Luo WH (2019) Bi-objective collaborative scheduling optimization of airport ferry vehicle and tractor. Int J Simul Model 18(2):355–365CrossRef Zhao PX, Gao WQ, Han X, Luo WH (2019) Bi-objective collaborative scheduling optimization of airport ferry vehicle and tractor. Int J Simul Model 18(2):355–365CrossRef
30.
Zurück zum Zitat Zhang H, Cui Y (2019) A model combining a Bayesian network with a modified genetic algorithm for green supplier selection. Simulation 95(12):1165–1183CrossRef Zhang H, Cui Y (2019) A model combining a Bayesian network with a modified genetic algorithm for green supplier selection. Simulation 95(12):1165–1183CrossRef
31.
Zurück zum Zitat Zhang H, Tang L, Yang C, Lan S (2019) Locating electric vehicle charging stations with service capacity using the improved whale optimization algorithm. Adv Eng Inform 41:100901CrossRef Zhang H, Tang L, Yang C, Lan S (2019) Locating electric vehicle charging stations with service capacity using the improved whale optimization algorithm. Adv Eng Inform 41:100901CrossRef
32.
Zurück zum Zitat Livieris IE, Pintelas P (2020) An improved weight-constrained neural network training algorithm. Neural Comput Appl 32:4177–4185CrossRef Livieris IE, Pintelas P (2020) An improved weight-constrained neural network training algorithm. Neural Comput Appl 32:4177–4185CrossRef
Metadaten
Titel
A combined deep learning method for internet car evaluation
verfasst von
Deming Li
Menggang Li
Gang Han
Ting Li
Publikationsdatum
27.08.2020
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 10/2021
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-020-05291-x

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