乐胖代购免代理版

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,9]],"date-time":"2024-07-09T12:01:53Z","timestamp":1720526513271},"reference-count":30,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers & Electrical Engineering"],"published-print":{"date-parts":[[2021,12]]},"DOI":"10.1016\/j.compeleceng.2021.107541","type":"journal-article","created":{"date-parts":[[2021,10,20]],"date-time":"2021-10-20T01:57:11Z","timestamp":1634695031000},"page":"107541","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":4,"special_numbering":"PB","title":["A comprehensive E-commerce customer behavior analysis using convolutional methods"],"prefix":"10.1016","volume":"96","author":[{"given":"Preeti","family":"Nagrath","sequence":"first","affiliation":[]},{"given":"Tu N.","family":"Nguyen","sequence":"additional","affiliation":[]},{"given":"Shivani","family":"Aggarwal","sequence":"additional","affiliation":[]},{"given":"D Jude","family":"Hemanth","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"2","key":"10.1016\/j.compeleceng.2021.107541_bib0001","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1109\/MIS.2016.31","article-title":"Affective computing and sentiment analysis","volume":"31","author":"Cambria","year":"2016","journal-title":"IEEE Intell Syst"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0002","series-title":"Proceedings of the international conference on machine learning","first-page":"2342","article-title":"An empirical exploration of recurrent network architectures","author":"Jozefowicz","year":"2015"},{"issue":"8","key":"10.1016\/j.compeleceng.2021.107541_bib0003","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long short-term memory","volume":"9","author":"Hochreiter","year":"1997","journal-title":"Neural Comput"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0004","series-title":"Proceedings of the conference on empirical methods in natural language processing (EMNLP 2014)","article-title":"Learning phrase representations using RNN encoder-decoder for statistical machine translation","author":"Cho","year":"2014"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0005","series-title":"Proceeding of the advances in neural information processing systems","first-page":"3856","article-title":"Dynamic routing between capsules","author":"Sabour","year":"2017"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0006","series-title":"Proceedings of the international conference on engineering and technology (ICET)","first-page":"1","article-title":"Understanding of a convolutional neural network","author":"Albawi","year":"2017"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0007","series-title":"Proceedings of the conference of the North American chapter of the association for computational linguistics: human language technologies","first-page":"1480","article-title":"Hierarchical attention networks for document classification","author":"Yang","year":"2016"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0008","article-title":"Bidirectional LSTM-CRF models for sequence tagging","author":"Huang","year":"2015","journal-title":"CORR J"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0009","doi-asserted-by":"crossref","unstructured":"Liu, S., Yang, N., Li, M., and Zhou, M.. 2014. A recursive recurrent neural network for statistical machine translation. In Proceedings of the 52nd annual meeting of the association for computational linguistics (1), pages 1491\u20131500.","DOI":"10.3115\/v1\/P14-1140"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0010","series-title":"Proceedings of the international conference on artificial neural networks","first-page":"44","article-title":"Transforming auto-encoders","author":"Hinton","year":"2011"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0011","series-title":"Proceedings of the NIPS 2014 workshop on deep learning","article-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling","author":"Chung","year":"2014"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0012","series-title":"Proceedings of the 57th annual meeting of the association for computational linguistics","first-page":"547","article-title":"Transfer capsule network for aspect level sentiment classification","author":"Chen","year":"2019"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0013","article-title":"Aspect-based sentiment analysis with new target representation and dependency attention","author":"Yang","year":"2019","journal-title":"IEEE Trans Affect Comput"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0014","doi-asserted-by":"crossref","DOI":"10.1109\/TKDE.2019.2947587","article-title":"Joint inference for aspect-level sentiment analysis by deep neural networks and linguistic hints","author":"Wang","year":"2019","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0015","series-title":"Proceedings of the IEEE international conference on innovative research and development (ICIRD)","first-page":"1","article-title":"Sentiment analysis on large scale Amazon product reviews","author":"Haque","year":"2018"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0016","article-title":"Offensive language analysis using deep learning architecture","author":"Ong","year":"2019","journal-title":"CORR J"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0017","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.future.2020.01.005","article-title":"Sentiment analysis of Twitter data during critical events through Bayesian networks classifiers","volume":"106","author":"Ruz","year":"2020","journal-title":"Future Gener Comput Syst"},{"issue":"11","key":"10.1016\/j.compeleceng.2021.107541_bib0018","doi-asserted-by":"crossref","first-page":"237","DOI":"10.3390\/fi11110237","article-title":"Feature fusion text classification model combining CNN and BiGRU with multi-attention mechanism","volume":"11","author":"Zhang","year":"2019","journal-title":"Future Internet"},{"issue":"5","key":"10.1016\/j.compeleceng.2021.107541_bib0019","doi-asserted-by":"crossref","first-page":"1091","DOI":"10.3233\/IDA-184311","article-title":"An attention-gated convolutional neural network for sentence classification","volume":"23","author":"Liu","year":"2019","journal-title":"Intell Data Anal"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0020","series-title":"Proceedings of the 3rd international conference on high performance compilation, computing and communications","first-page":"33","article-title":"A text sentiment analysis model based on self-attention mechanism","author":"Ji","year":"2019"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0021","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1016\/j.neucom.2019.10.033","article-title":"Text classification using capsules","volume":"376","author":"Kim","year":"2020","journal-title":"Neurocomputing"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0022","first-page":"1","article-title":"Deep refinement: capsule network with attention mechanism-based system for text classification","author":"Jain","year":"2019","journal-title":"Neural Comput Appl"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0023","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.neunet.2019.06.014","article-title":"Investigating the transferring capability of capsule networks for text classification","volume":"118","author":"Yang","year":"2019","journal-title":"Neural Netw"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0024","series-title":"Proceedings of the conference on empirical methods in natural language processing and the 9th international joint conference on natural language processing (EMNLP-IJCNLP)","first-page":"188","article-title":"Justifying recommendations using distantly-labeled reviews and fine-grained aspects","author":"Ni","year":"2019"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0025","series-title":"Proceedings of the EMNLP workshop BlackboxNLP: analyzing and interpreting neural networks for NLP","first-page":"267","article-title":"Importance of self-attention for sentiment analysis","author":"Letarte","year":"2018"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0026","doi-asserted-by":"crossref","first-page":"49558","DOI":"10.1109\/ACCESS.2019.2910584","article-title":"Data capsule: representation of heterogeneous data in cloud-edge computing","volume":"7","author":"Filip","year":"2019","journal-title":"IEEE Access"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0027","unstructured":"Ye, Q., Fan, X., Fang, G., Bie, H., Xiang, C., Song, X., & He, X. (2020). EdgeLoc: an edge-IoT framework for robust indoor localization using capsule networks. arXiv preprint arXiv:2009.05780."},{"key":"10.1016\/j.compeleceng.2021.107541_bib0028","doi-asserted-by":"crossref","first-page":"e3789","DOI":"10.1002\/ett.3789","article-title":"HIT4Mal: hybrid image transformation for malware classification","volume":"31","author":"Vu","year":"2020","journal-title":"Trans Emerg Telecommun Technol"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0029","first-page":"6602","volume":"8","author":"Le","year":"2020"},{"key":"10.1016\/j.compeleceng.2021.107541_bib0030","series-title":"Proceedings of the 6th NAFOSTED conference on information and computer science (NICS)","first-page":"234","article-title":"A convolutional transformation network for malware classification","author":"Vu","year":"2019"}],"container-title":["Computers & Electrical Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0045790621004869?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0045790621004869?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2023,11,11]],"date-time":"2023-11-11T11:30:38Z","timestamp":1699702238000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0045790621004869"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12]]},"references-count":30,"alternative-id":["S0045790621004869"],"URL":"https:\/\/doi.org\/10.1016\/j.compeleceng.2021.107541","relation":{},"ISSN":["0045-7906"],"issn-type":[{"value":"0045-7906","type":"print"}],"subject":[],"published":{"date-parts":[[2021,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A comprehensive E-commerce customer behavior analysis using convolutional methods","name":"articletitle","label":"Article Title"},{"value":"Computers & Electrical Engineering","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.compeleceng.2021.107541","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2021 Elsevier Ltd. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"107541"}}