PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Active learning for automatic classification of complaints about municipal waste management

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Information flow is an important issue in the area of waste management. There is a need for a fast response to reported problems. Therefore we investigated the classification process of Polish wasterelated complaints sent by Wrocław’s residents. It has been noticed that residents, mostly without expert knowledge of waste management, incorrectly classify the observed problems. In response to the observed unacceptable classification accuracy, we introduced a multi-class machine learning classification. Machine learning is widely used in waste management issues like predicting waste generation or different waste fractions identification for automated sorting. However, based on the literature review, it can be stated that there is a lack of solutions in machine learning-based text classification regarding waste management. Ten chosen classifiers were used to classify considered complaints into defined categories automatically. Additionally, we incorporated the active learning approach to reduce experts' effort involved in the labeling process, which is necessary when having an unlabeled dataset. The results confirm the possibility of applying machine learning algorithms to waste-related Polish complaints.
Rocznik
Strony
53--66
Opis fizyczny
Bibliogr. 25 poz., rys., tab.
Twórcy
autor
  • Faculty of Mechanical Engineering, Department of Operation and Maintenance of Technical Systems, Wrocław University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland
  • Faculty of Mechanical Engineering, Department of Operation and Maintenance of Technical Systems, Wrocław University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland
  • Faculty of Mechanical Engineering, Department of Operation and Maintenance of Technical Systems, Wrocław University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland
Bibliografia
  • [1] PASIECZNIK I., BANASZKIEWICZ K., SYSKA Ł., Local community e-waste awareness and bahavior. Polish case study, Environ. Prot. Eng., 2017, 43 (3), 287–303. DOI: 10.37190/epe170320.
  • [2] JAKUBUS M., STEJSKAL B., Municipal solid waste management systems in Poland and the Czech Republic. A comparative study, Environ. Prot. Eng., 2020, 46 (3), 61–78. DOI: 10.37190/epe200304.
  • [3] SARC R., CURTIS A., KANDLBAUER L., KHODIER K., LORBER K.E., POMBERGER R., Digitalisation and intelligent robotics in value chain of circular economy oriented waste management. A review, Waste Manage., 2019, 95, 476–492. DOI: 10.1016/j.wasman.2019.06.035.
  • [4] The Early Warning report for Poland Accompanying the document. Report from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions on the implementation of EU waste legislation, SWD (2018) 426 final. Brussels. DOI: 10.1017/CBO9781107415324.004.
  • [5] Directive (EU) 2018/850 of the European Parliament and of the Council of 30 May 2018 amending Directive 1999/31/EC on the landfill of waste. Retrieved from http://data.europa.eu/eli/dir/2018/850/oj.
  • [6] MONTEBRUNO P., BENNETT R.J., SMITH H., VAN LIESHOUT C., Machine learning classification of entrepreneurs in British historical census data, Inf. Proc. Manage., 2020, 57 (3), 1–22. DOI:10.1016/j.ipm.2020.102210.
  • [7] HACOHEN-KERNER Y., DILMON R., HONE M., BEN-BASAN M.A., Automatic classification of complaintletters according to service provider categories, Inf. Proc. Manage., 2019, 56 (6), 1–20. DOI: 10.1016/j.ipm.2019.102102.
  • [8] KO Y., SEO J., Text classification from unlabeled documents with bootstrapping and feature projection techniques, Inf. Proc. Manage., 2009, 45 (1), 70–83. DOI: 10.1016/j.ipm.2008.07.004.
  • [9] ZHOU Y., YANG S., LI Y., CHEN Y., YAO J., QAZI A., Does the review deserve more helpfulness when its title resembles the content? Locating helpful reviews by text mining, Inf. Proc. Manage., 2020, 57 (2), 1–11. DOI: 10.1016/j.ipm.2019.102179.
  • [10] KOZLOWSKI D., LANNELONGUE E., SAUDEMONT F., BENAMARA F., MARI A., MORICEAU V., BOUMADANE A., A three-level classification of French tweets in ecological crises, Inf. Proc. Manage., 2020, 57 (5), 1–20. DOI: 10.1016/j.ipm.2020.102065284.
  • [11] LI L., LI W., GONG D., Naive Bayesian automatic classification of railway service complaint text basedon eigenvalue extraction, TV-TG, 2019, 26 (3), 778–785. DOI: 10.17559/TV-20190420161815.
  • [12] BAGHERI M., ESFILAR R., GOLCHI M.S., KENNEDY C.A., A comparative data mining approach for the prediction of energy recovery potential from various municipal solid waste, Renew. Sustain. Energy Rev., 2019, 116, 1–12. DOI: 10.1016/j.rser.2019.109423.
  • [13] FERRER J., ALBA E., BIN-CT: Urban waste collection based on predicting the container fill level, Biosyst., 2019, 186, 1–9. DOI: 10.1016/j.biosystems.2019.04.006.
  • [14] PRASANNA M.A., VIKASH KAUSHAL S., MAHALAKSHMI P., Survey on identification and classification of waste for efficient disposal and recycling, Int. J. Eng. Technol., 2018, 7 (2.8), 520–523. DOI: 10.14419/ijet.v7i2.8.10513.
  • [15] KANNANGARA M., DUA R., AHMADI L., BENSEBAA F., Modeling and prediction of regional municipal solid waste generation and diversion in Canada using machine learning approaches, Waste Manage., 2018, 74, 3–15. DOI: 10.1016/j.wasman.2017.11.057.
  • [16] DIMILILER K., EVER Y.K., MUSTAFA S.M., Vehicle detection and tracking using machine learning techniques, 10th Int. Conf. Theory and Application of Soft Computing with Words and Perceptions – ICSCCW, 2020, 373–381. 10.1007/978-3-030-35249-3_48.
  • [17] MALINAUSKAITE J., JOUHARA H., CZAJCZYŃSKA D., STANCHEV P., KATSOU E., ROSTKOWSKI P., THORNE R.J., COLON J., PONSA S., AL-MANSOUR F., ANGUILANO L, KRZYŻYŃSKA R., LOPEZ J.C., VLASOPOULOS A., SPENCER N., Municipal solid waste management and waste-to-energy in the context of a circular economy and energy recycling in Europe, Energy, 2017, 141, 2013–2044. DOI: 10.1016/j.energy.2017.11.128.
  • [18] ZHANG A., VENKATESH V.G., LIU Y., WAN M., QU T., HUISINGH D., Barriers to smart waste management for a circular economy in China, J. Clean. Prod, 2019, 240, 1–12. DOI: 10.1016/j.jclepro. 2019.118198.
  • [19] ALLAHYARI M., POURIYEH S., ASSEFI M., SAFAEI S., TRIPPE E.D., GUTIERREZ J.B., KOCHUT K., A brief survey of text mining: Classification, clustering and extraction techniques, ArXiv, 2017, 1–13. DOI: http://arxiv.org/abs/1707.02919.
  • [20] DZISEVIC R., SESOK D., Text classification using different feature extraction approaches, Open Conference of Electrical, Electronic and Information Sciences, eStream 2019, Proc. IEEE, 1–4. DOI:10.1109/eStream.2019.8732167.
  • [21] KADHIM A.I., Survey on supervised machine learning techniques for automatic text classification, Artif. Intell. Rev., 2019, 52 (1), 273–292. DOI: 10.1007/s10462-018-09677-1.
  • [22] KOWSARI K., MEIMANDI K.J., HEIDARYSAFA M., MENDU S., BARNES L.E., BROWN D.E., Text classification algorithms: A survey, Information (Switzerland), 2019, 10 (4), 1–68. DOI: 10.3390/info10040150.
  • [23] SOKOLOVA M., LAPALME G., A systematic analysis of performance measures for classification tasks, Inf. Proc.. Manage., 2009, 45 (4), 427–437. DOI: 10.1016/j.ipm.2009.03.002.
  • [24] BEHERA B., KUMARAVELAN G., KUMAR P., Performance evaluation of deep learning algorithms in biomedical document classification, 11th Int. Conf. Advanced Computing (ICoAC), Chennai, India, 2019, 2020–2024. DOI: 10.1109/ICoAC48765.2019.246843.
  • [25] DĄBROWSKA A., GIEL R., PLEWA M., Assessment of the municipal waste collection process on the basis of irregularities notifications sent by residents. A case study in Wroclaw, Poland, Environ. Prot. Eng., 2020, 46 (2), 79–92. DOI: 10.37190/epe200206.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-c7fba8e0-8ad6-4ebf-8d85-39b028cdd250
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.