{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T14:00:46Z","timestamp":1762351246917,"version":"3.37.3"},"reference-count":59,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2019,7,29]],"date-time":"2019-07-29T00:00:00Z","timestamp":1564358400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,7,29]],"date-time":"2019-07-29T00:00:00Z","timestamp":1564358400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772021","11371014","61772420"],"award-info":[{"award-number":["61772021","11371014","61772420"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2020,2]]},"DOI":"10.1007\/s13042-019-00987-6","type":"journal-article","created":{"date-parts":[[2019,7,29]],"date-time":"2019-07-29T06:02:22Z","timestamp":1564380142000},"page":"475-490","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Unlabelled text mining methods based on two extension models of concept lattices"],"prefix":"10.1007","volume":"11","author":[{"given":"Xiaoyu","family":"Chen","sequence":"first","affiliation":[]},{"given":"Jianjun","family":"Qi","sequence":"additional","affiliation":[]},{"given":"Xiaomin","family":"Zhu","sequence":"additional","affiliation":[]},{"given":"Xin","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Zhen","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,7,29]]},"reference":[{"key":"987_CR1","unstructured":"Lewis DD (1992) Representation and learning in information retrieval. Dissertation, University of Massachusetts"},{"key":"987_CR2","doi-asserted-by":"crossref","unstructured":"Yang WC, Wu QW, Cheng ZS (2017) Research on distributed text clustering based on frequent itemset. In: 36th Chinese Control Conference, pp. 5700\u20135705","DOI":"10.23919\/ChiCC.2017.8028263"},{"key":"987_CR3","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.knosys.2015.06.015","volume":"89","author":"K Ravi","year":"2015","unstructured":"Ravi K, Ravi V (2015) A survey on opinion mining and sentiment analysis: tasks, approaches and applications. Knowl-Based Syst 89:14\u201346","journal-title":"Knowl-Based Syst"},{"key":"987_CR4","unstructured":"Mccallum A, Nigam K (1998) Employing EM and Pool-Based active learning for text classification. In: Proceedings of the 15th international conference on machine learning, pp 350\u2013358"},{"key":"987_CR5","unstructured":"Kandola J, Shawe-Taylor J, Cristianini N (2002) Learning semantic similarity. In: NIPS, pp 673\u2013680"},{"key":"987_CR6","first-page":"445","volume-title":"NATO Advanced Study Institutes Series","author":"R Wille","year":"1982","unstructured":"Wille R (1982) Restructuring lattice theory: an approach based on hierarchies of concepts. In: Rival I (ed) NATO Advanced Study Institutes Series. Springer, Berlin, pp 445\u2013470"},{"key":"987_CR7","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-642-59830-2","volume-title":"Formal concept analysis: mathematical foundations (Chap 1)","author":"B Ganter","year":"1999","unstructured":"Ganter B, Wille R (1999) Formal concept analysis: mathematical foundations (Chap 1). Springer, New York"},{"key":"987_CR8","doi-asserted-by":"crossref","unstructured":"Tang J, He W, Zhang W, Fan L (2010) An algorithm of extracting classification rule based on classified concept lattice. In: Proceedings of the 2nd international workshop on database technology and applications, Wuhan, pp 1\u20134","DOI":"10.1109\/DBTA.2010.5658971"},{"issue":"12","key":"987_CR9","first-page":"1415","volume":"37","author":"Z Xie","year":"2000","unstructured":"Xie Z, Liu Z (2000) Concept lattice and association rule discovery. J Comput Res Dev 37(12):1415\u20131421","journal-title":"J Comput Res Dev"},{"issue":"3","key":"987_CR10","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1080\/08839514.2012.648457","volume":"26","author":"CA Kumar","year":"2012","unstructured":"Kumar CA (2012) Fuzzy clustering-based formal concept analysis for association rules mining. Appl Artif Intell 26(3):274\u2013301","journal-title":"Appl Artif Intell"},{"issue":"11","key":"987_CR11","doi-asserted-by":"crossref","first-page":"1879","DOI":"10.1007\/s13042-018-0794-9","volume":"9","author":"A Houari","year":"2018","unstructured":"Houari A, Ayadi W, Ben Yahia S (2018) A new FCA-based method for identifying biclusters in gene expression data. Int J Mach Learn Cybern 9(11):1879\u20131893","journal-title":"Int J Mach Learn Cybern"},{"issue":"1","key":"987_CR12","first-page":"34","volume":"12","author":"CA Kumar","year":"2012","unstructured":"Kumar CA, Radavansky M, Annapurna J (2012) Analysis of vector space model, latent semantic indexing and formal concept analysis for information retrieval. Cybern Inf Technol 12(1):34\u201348","journal-title":"Cybern Inf Technol"},{"issue":"3","key":"987_CR13","doi-asserted-by":"crossref","first-page":"2696","DOI":"10.1016\/j.eswa.2009.09.026","volume":"37","author":"CA Kumar","year":"2010","unstructured":"Kumar CA, Srinivas S (2010) Concept lattice reduction using fuzzy K-means clustering. Expert Syst Appl 37(3):2696\u20132704","journal-title":"Expert Syst Appl"},{"issue":"11","key":"987_CR14","doi-asserted-by":"crossref","first-page":"1895","DOI":"10.1007\/s13042-017-0698-0","volume":"9","author":"X Kang","year":"2018","unstructured":"Kang X, Miao D, Lin G, Liu Y (2018) Relation granulation and algebraic structure based on concept lattice in complex information systems. Int J Mach Learn Cybern 9(11):1895\u20131907","journal-title":"Int J Mach Learn Cybern"},{"key":"987_CR15","unstructured":"Richards D, Compton P (1997) Combining formal concept analysis and ripple down rules to support reuse. In: Proceedings of Software Engineering Knowledge Engineering SEKE 1997, Madrid, Springer, Heidelberg"},{"issue":"2","key":"987_CR16","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1515\/amcs-2016-0035","volume":"26","author":"PK Singh","year":"2016","unstructured":"Singh PK, Kumar CA, Gani A (2016) A comprehensive survey on formal concept analysis, its research trends and applications. Int J Appl Math Comput Sci 26(2):495\u2013516","journal-title":"Int J Appl Math Comput Sci"},{"issue":"2","key":"987_CR17","doi-asserted-by":"crossref","first-page":"715","DOI":"10.1007\/s10115-018-1252-4","volume":"60","author":"A Formica","year":"2019","unstructured":"Formica A (2019) Similarity reasoning in formal concept analysis: from one- to many-valued contexts. Knowl Inf Syst 60(2):715\u2013739","journal-title":"Knowl Inf Syst"},{"issue":"5","key":"987_CR18","doi-asserted-by":"crossref","first-page":"553","DOI":"10.1006\/ijhc.1996.0067","volume":"45","author":"C Carpineto","year":"1996","unstructured":"Carpineto C, Romano G (1996) Information retrieval through hybrid navigation of lattice representations. Int J Hum Comput Stud 45(5):553\u2013578","journal-title":"Int J Hum Comput Stud"},{"key":"987_CR19","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1007\/978-3-540-39804-2_21","volume-title":"Knowledge Discovery in Databases: PKDD 2003","author":"Andreas Hotho","year":"2003","unstructured":"Hotho A, Staab S, Stumme G (2003) Explaining text clustering results using semantic structures. In: European Conference on Principles of Data Mining and Knowledge Discovery,\u00a0PKDD 2003 (LNCS 2838), pp 217\u2013228"},{"key":"987_CR20","unstructured":"Huang L (2005) Study on search results clustering based on formal concept analysis. Dissertation, Huazhong University"},{"issue":"1","key":"987_CR21","first-page":"114","volume":"16","author":"N Wang","year":"2006","unstructured":"Wang N, Li YS (2006) Text mining based on concept lattice. Comput Technol Dev 16(1):114\u2013116","journal-title":"Comput Technol Dev"},{"key":"987_CR22","first-page":"625","volume":"6\u20137","author":"HS Xu","year":"2012","unstructured":"Xu HS (2012) Construction search engine based on formal concept analysis and association rule mining. Adv Eng Forum 6\u20137:625\u2013630","journal-title":"Adv Eng Forum"},{"key":"987_CR23","unstructured":"Liu JJ (2013) Research on semantic information retrieval model based on concept lattice. Dissertation, Jilin University"},{"key":"987_CR24","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-642-60460-7","volume-title":"Fuzzy-Begriffe: formale begriffsanalyse unscharfer daten","author":"S Pollandt","year":"1997","unstructured":"Pollandt S (1997) Fuzzy-Begriffe: formale begriffsanalyse unscharfer daten. Springer, Berlin"},{"issue":"1\u20133","key":"987_CR25","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/j.apal.2003.01.001","volume":"128","author":"R B\u0115lohl\u00e1vek","year":"2004","unstructured":"B\u0115lohl\u00e1vek R (2004) Concept lattices and order in fuzzy logic. Ann Pure Appl Logic 128(1\u20133):277\u2013298","journal-title":"Ann Pure Appl Logic"},{"key":"987_CR26","doi-asserted-by":"crossref","unstructured":"B\u0115lohl\u00e1vek R (2005) What is a fuzzy concept lattice? In: Proceedings of international conference on rough sets, Fuzzy Sets, Data Mining and Granular Computing, pp 19\u201326","DOI":"10.1007\/978-3-642-21881-1_4"},{"key":"987_CR27","doi-asserted-by":"crossref","first-page":"726","DOI":"10.1007\/978-3-540-30475-3_50","volume-title":"The Semantic Web \u2013 ISWC 2004","author":"Thanh Tho Quan","year":"2004","unstructured":"Quan TT, Hui SC, Fong ACM, Cao TH (2004) Automatic generation of ontology for scholarly semantic web. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol 3298. Springer, Berlin, pp. 726\u2013740"},{"issue":"3\u20134","key":"987_CR28","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1007\/BF00485052","volume":"30","author":"LA Zadeh","year":"1975","unstructured":"Zadeh LA (1975) Fuzzy logic and approximate reasoning (in memory of Grigore Moisil). Synthese 30(3\u20134):407\u2013428","journal-title":"Synthese"},{"key":"987_CR29","doi-asserted-by":"crossref","first-page":"689","DOI":"10.1016\/j.future.2017.08.044","volume":"82","author":"CF Zou","year":"2018","unstructured":"Zou CF, Deng HF, Wan JF, Wang ZR, Deng P (2018) Mining and updating association rules based on fuzzy concept lattice. Future Gener Comp Syst 82:689\u2013706","journal-title":"Future Gener Comp Syst"},{"key":"987_CR30","doi-asserted-by":"crossref","first-page":"786","DOI":"10.1016\/j.asoc.2017.05.028","volume":"60","author":"K Ravi","year":"2017","unstructured":"Ravi K, Vadlamani R, Prasad PSRK (2017) Fuzzy formal concept analysis based opinion mining for CRM in financial services. Appl Soft Comput 60:786\u2013807","journal-title":"Appl Soft Comput"},{"key":"987_CR31","first-page":"1","volume-title":"Handbook on ontologies","author":"N Guarino","year":"2010","unstructured":"Guarino N, Oberle D, Staab S (2010) What is an ontology? In: Staab S, Studer R (eds) Handbook on ontologies. Springer, Berlin, pp 1\u201317"},{"issue":"8","key":"987_CR32","first-page":"188","volume":"36","author":"Q Yang","year":"2010","unstructured":"Yang Q, Chen W, Wen B (2010) Fuzzy ontology model for semantic information query. Comput Eng 36(8):188\u2013190","journal-title":"Comput Eng"},{"issue":"4","key":"987_CR33","first-page":"1537","volume":"33","author":"HL Li","year":"2012","unstructured":"Li HL, Liu N, Li GY (2012) Concept distance clustering method of generating fuzzy ontology. Comput Eng Des 33(4):1537\u20131538","journal-title":"Comput Eng Des"},{"issue":"3","key":"987_CR34","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1016\/j.ipm.2011.04.003","volume":"48","author":"CD Maio","year":"2012","unstructured":"Maio CD, Fenza G, Loia V, Senatore S (2012) Hierarchical web resources retrieval by exploiting fuzzy formal concept analysis. Inf Process Manage 48(3):399\u2013418","journal-title":"Inf Process Manage"},{"issue":"2","key":"987_CR35","doi-asserted-by":"crossref","first-page":"1908","DOI":"10.1016\/j.asoc.2010.06.007","volume":"11","author":"RC Chen","year":"2011","unstructured":"Chen RC, Bau CT, Yeh CJ (2011) Merging domain ontologies based on the WordNet system and fuzzy formal concept analysis techniques. Appl Soft Comput 11(2):1908\u20131923","journal-title":"Appl Soft Comput"},{"issue":"24","key":"987_CR36","doi-asserted-by":"crossref","first-page":"1","DOI":"10.17485\/ijst\/2015\/v8i31\/84085","volume":"8","author":"M Priya","year":"2015","unstructured":"Priya M, Kumar CA (2015) A survey of state of the art of Ontology construction and merging using formal concept analysis. Indian J Sci Technol 8(24):1\u20137","journal-title":"Indian J Sci Technol"},{"key":"987_CR37","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.knosys.2015.11.017","volume":"95","author":"F Bobillo","year":"2015","unstructured":"Bobillo F, Straccia U (2015) The fuzzy ontology reasoner fuzzyDL. Knowl-Based Syst 95:12\u201334","journal-title":"Knowl-Based Syst"},{"key":"987_CR38","unstructured":"Macqueen J (1965) Some methods for classification and analysis of multiVariate observations. In: Proceedings of the 5th berkeley symposium on mathematical statistics and probability, pp 281\u2013297"},{"issue":"1","key":"987_CR39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TPAMI.1980.4766964","volume":"2","author":"JC Bezdek","year":"1980","unstructured":"Bezdek JC (1980) A convergence theorem for the fuzzy isodata clustering algorithms. IEEE Trans Patt Anal Machine IntelL 2(1):1\u20138","journal-title":"IEEE Trans Patt Anal Machine IntelL"},{"key":"987_CR40","first-page":"115","volume":"25","author":"CF Gao","year":"2010","unstructured":"Gao CF, Wu XJ, Zhang SS (2010) An improved semi-supervised fuzzy clustering algorithm. Control Decis 25:115\u2013120","journal-title":"Control Decis"},{"issue":"6","key":"987_CR41","first-page":"856","volume":"32","author":"JB Huang","year":"2005","unstructured":"Huang JB, Ji HB (2005) A web search results clustering algorithm based on fuzzy concept lattices. J Xidian Univ 32(6):856\u2013860","journal-title":"J Xidian Univ"},{"key":"987_CR42","doi-asserted-by":"crossref","unstructured":"Zhou W, Liu Z, Zhao Y (2007) Ontology learning by clustering based on fuzzy formal concept analysis. In: Proceedings of the 31st annual international computer software and applications conference, pp 204\u2013210","DOI":"10.1109\/COMPSAC.2007.161"},{"key":"987_CR43","unstructured":"Liu B, Hsu W, Ma Y (1998) Integrating classification and association rule mining. In: Proceedings of the fourth international conference on knowledge discovery and data mining (KDD\u201998), pp 80\u201386"},{"issue":"5","key":"987_CR44","doi-asserted-by":"crossref","first-page":"1638","DOI":"10.1109\/TFUZZ.2014.2371479","volume":"23","author":"XZ Wang","year":"2015","unstructured":"Wang XZ, Xing HJ, Li Y et al (2015) A study on relationship between generalization abilities and fuzziness of base classifiers in ensemble learning. IEEE Trans Fuzzy Syst 23(5):1638\u20131654","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"2","key":"987_CR45","doi-asserted-by":"crossref","first-page":"703","DOI":"10.1109\/TCYB.2017.2653223","volume":"48","author":"XZ Wang","year":"2018","unstructured":"Wang XZ, Wang R, Xu C (2018) Discovering the relationship between generalization and uncertainty by incorporating complexity of classification. IEEE Trans Cybern 48(2):703\u2013715","journal-title":"IEEE Trans Cybern"},{"issue":"6","key":"987_CR46","doi-asserted-by":"crossref","first-page":"1460","DOI":"10.1109\/TFUZZ.2017.2717803","volume":"25","author":"R Wang","year":"2017","unstructured":"Wang R, Wang XZ, Kwong S, Xu C (2017) Incorporating diversity and informativeness in multiple-instance active learning. IEEE Trans Fuzzy Syst 25(6):1460\u20131475","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"7","key":"987_CR47","doi-asserted-by":"crossref","first-page":"1299","DOI":"10.1109\/TSMC.2017.2701419","volume":"49","author":"XZ Wang","year":"2019","unstructured":"Wang XZ, Zhang TL, Wang R (2019) Noniterative deep learning: incorporating restricted Boltzmann machine into multilayer random weight neural networks. IEEE Trans Syst Man Cybern Syst 49(7):1299\u20131308","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"987_CR48","first-page":"343","volume-title":"Lecture Notes in Computer Science","author":"Mehran Sahami","year":"1995","unstructured":"Sahami M (1995) Learning classification rules using lattices (extended abstract). In: Proceedings of the 8th European conference on machine learning, pp 343\u2013346"},{"key":"987_CR49","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1007\/11510888_2","volume-title":"Machine Learning and Data Mining in Pattern Recognition","author":"Anamika Gupta","year":"2005","unstructured":"Gupta, A., Kumar, N., Bhatnagar (2005) Incremental classification rules based on association rules using formal concept analysis. In: Perner, P., Imiya, A. (eds.) MLDM. LNCS (LNAI), vol 3587. Springer, Berlin, pp. 11\u201320"},{"key":"987_CR50","doi-asserted-by":"crossref","first-page":"690","DOI":"10.1007\/978-3-642-24553-4_91","volume-title":"Bio-Inspired Computing and Applications","author":"Junhong Wang","year":"2012","unstructured":"Wang J, Liang J, Qian Y (2011) Closed-Label concept lattice based rule extraction approach. In: International conference on intelligent computing: bio-Inspired computing and applications, pp 690\u2013698"},{"key":"987_CR51","doi-asserted-by":"crossref","first-page":"732","DOI":"10.1007\/978-3-319-11740-9_67","volume":"8818","author":"J Qi","year":"2014","unstructured":"Qi J, Wei L, Yao Y (2014) Three-Way formal concept analysis. Lect Notes Comput Sci 8818:732\u2013741","journal-title":"Lect Notes Comput Sci"},{"key":"987_CR52","doi-asserted-by":"crossref","unstructured":"Wei L, Qian T (2015) The three-way object oriented concept lattice and the three-way property oriented concept lattice. In: International conference on machine learning and cybernetics, pp 854\u2013859","DOI":"10.1109\/ICMLC.2015.7340665"},{"key":"987_CR53","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.knosys.2016.01.045","volume":"99","author":"RS Ren","year":"2016","unstructured":"Ren RS, Wei L (2016) The attribute reductions of three-way concept lattices. Knowl-Based Syst 99:92\u2013102","journal-title":"Knowl-Based Syst"},{"key":"987_CR54","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/j.knosys.2015.08.006","volume":"91","author":"J Qi","year":"2016","unstructured":"Qi J, Qian T, Wei L (2016) The connections between three-way and classical concept lattices. Knowl-Based Syst 91:143\u2013151","journal-title":"Knowl-Based Syst"},{"key":"987_CR55","doi-asserted-by":"crossref","first-page":"218","DOI":"10.1016\/j.ijar.2017.01.009","volume":"83","author":"C Huang","year":"2017","unstructured":"Huang C, Li J, Mei C, Wu W (2017) Three-way concept learning based on cognitive operators: an information fusion viewpoint. Int J Approx Reason 83:218\u2013242","journal-title":"Int J Approx Reason"},{"key":"987_CR56","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1016\/j.ins.2016.04.051","volume":"378","author":"J Li","year":"2017","unstructured":"Li J, Huang C, Qi J, Qian Y, Liu W (2017) Three-way cognitive concept learning via multi-granularity. Inf Sci 378:244\u2013263","journal-title":"Inf Sci"},{"issue":"11","key":"987_CR57","doi-asserted-by":"crossref","first-page":"1807","DOI":"10.1007\/s13042-018-0840-7","volume":"9","author":"SC Mouliswaran","year":"2018","unstructured":"Mouliswaran SC, Kumar CA, Chandrasekar C (2018) Role based access control design using three-way formal concept analysis. Int J Mach Learn Cybern 9(11):1807\u20131837","journal-title":"Int J Mach Learn Cybern"},{"key":"987_CR58","first-page":"27","volume-title":"Lecture Notes in Computer Science","author":"Maria-Luiza Antonie","year":"2004","unstructured":"Antonie ML, Za\u00efane OR (2004) Mining positive and negative association rules: an approach for confined rules. In: Principles and practice of knowledge discovery in databases, vol 3202, pp. 27\u201338"},{"key":"987_CR59","unstructured":"Sogou. Sogou Labs[DB\/OL]. \nhttp:\/\/www.sogou.com\/labs\/resource\/list_news.php.2017\n\n."}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-019-00987-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s13042-019-00987-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-019-00987-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,7,27]],"date-time":"2020-07-27T23:46:09Z","timestamp":1595893569000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s13042-019-00987-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,29]]},"references-count":59,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2020,2]]}},"alternative-id":["987"],"URL":"https:\/\/doi.org\/10.1007\/s13042-019-00987-6","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"type":"print","value":"1868-8071"},{"type":"electronic","value":"1868-808X"}],"subject":[],"published":{"date-parts":[[2019,7,29]]},"assertion":[{"value":"28 October 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 July 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 July 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}