{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T11:36:42Z","timestamp":1765280202356},"reference-count":46,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2020,9,30]],"date-time":"2020-09-30T00:00:00Z","timestamp":1601424000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,9,30]],"date-time":"2020-09-30T00:00:00Z","timestamp":1601424000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2021,3]]},"DOI":"10.1007\/s13042-020-01202-7","type":"journal-article","created":{"date-parts":[[2020,9,30]],"date-time":"2020-09-30T16:03:02Z","timestamp":1601481782000},"page":"783-806","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["A parallel hybrid krill herd algorithm for feature selection"],"prefix":"10.1007","volume":"12","author":[{"given":"Laith","family":"Abualigah","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bisan","family":"Alsalibi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammad","family":"Shehab","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammad","family":"Alshinwan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ahmad M.","family":"Khasawneh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hamzeh","family":"Alabool","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,9,30]]},"reference":[{"key":"1202_CR1","doi-asserted-by":"crossref","unstructured":"Al-Sai ZA, Abualigah LM (2017) Big data and e-government: A review. In: Information Technology (ICIT), 2017 8th International Conference on, IEEE, pp 580\u2013587","DOI":"10.1109\/ICITECH.2017.8080062"},{"key":"1202_CR2","doi-asserted-by":"crossref","unstructured":"Peng H, Wang C, Guan X (2010) Swarm intelligent optimization algorithm for text clustering. In: 2010 3rd International Conference on Computer Science and Information Technology, volume\u00a05, IEEE, pp 200\u2013203","DOI":"10.1109\/ICCSIT.2010.5565020"},{"key":"1202_CR3","doi-asserted-by":"publisher","first-page":"4773","DOI":"10.1007\/s11227-017-2046-2","volume":"73","author":"LM Abualigah","year":"2017","unstructured":"Abualigah LM, Khader AT (2017) Unsupervised text feature selection technique based on hybrid particle swarm optimization algorithm with genetic operators for the text clustering. The Journal of Supercomputing 73:4773\u20134795","journal-title":"The Journal of Supercomputing"},{"key":"1202_CR4","doi-asserted-by":"publisher","first-page":"192","DOI":"10.1016\/j.eswa.2019.05.030","volume":"134","author":"R Janani","year":"2019","unstructured":"Janani R, Vijayarani S (2019) Text document clustering using spectral clustering algorithm with particle swarm optimization. Expert Systems with Applications 134:192\u2013200","journal-title":"Expert Systems with Applications"},{"key":"1202_CR5","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1007\/s00521-017-2988-6","volume":"31","author":"GI Sayed","year":"2019","unstructured":"Sayed GI, Hassanien AE, Azar AT (2019) Feature selection via a novel chaotic crow search algorithm. Neural Computing and Applications 31:171\u2013188","journal-title":"Neural Computing and Applications"},{"key":"1202_CR6","doi-asserted-by":"publisher","first-page":"19","DOI":"10.5121\/ijcsea.2015.5102","volume":"5","author":"LMQ Abualigah","year":"2015","unstructured":"Abualigah LMQ, Hanandeh ES (2015) Applying genetic algorithms to information retrieval using vector space model. International Journal of Computer Science, Engineering and Applications 5:19","journal-title":"International Journal of Computer Science, Engineering and Applications"},{"key":"1202_CR7","doi-asserted-by":"crossref","unstructured":"Zhang Y, Li H-G, Wang Q, Peng C (2019) A filter-based bare-bone particle swarm optimization algorithm for unsupervised feature selection. Applied Intelligence 1\u201310","DOI":"10.1007\/s10489-019-01420-9"},{"key":"1202_CR8","doi-asserted-by":"publisher","first-page":"1688","DOI":"10.1007\/s10489-018-1334-8","volume":"49","author":"M Tubishat","year":"2019","unstructured":"Tubishat M, Abushariah MA, Idris N, Aljarah I (2019) Improved whale optimization algorithm for feature selection in arabic sentiment analysis. Applied Intelligence 49:1688\u20131707","journal-title":"Applied Intelligence"},{"key":"1202_CR9","doi-asserted-by":"crossref","unstructured":"Abualigah LM, Khader AT (2016) AI-Betar MA, Unsupervised feature selection technique based on harmony search. In: 2016 7th international conference on computer science and information technology (CSIT), IEEE","DOI":"10.1109\/CSIT.2016.7549456"},{"key":"1202_CR10","doi-asserted-by":"publisher","first-page":"1423","DOI":"10.1007\/s11676-017-0555-8","volume":"29","author":"E Hazir","year":"2018","unstructured":"Hazir E, Erdinler ES, Koc KH (2018) Optimization of cnc cutting parameters using design of experiment (doe) and desirability function. Journal of forestry research 29:1423\u20131434","journal-title":"Journal of forestry research"},{"key":"1202_CR11","doi-asserted-by":"publisher","first-page":"944","DOI":"10.1109\/TNNLS.2017.2650978","volume":"29","author":"M Luo","year":"2018","unstructured":"Luo M, Nie F, Chang X, Yang Y, Hauptmann AG, Zheng Q (2018) Adaptive unsupervised feature selection with structure regularization. IEEE transactions on neural networks and learning systems 29:944\u2013956","journal-title":"IEEE transactions on neural networks and learning systems"},{"key":"1202_CR12","doi-asserted-by":"publisher","first-page":"5197","DOI":"10.1016\/j.eswa.2010.10.041","volume":"38","author":"M Zhao","year":"2011","unstructured":"Zhao M, Fu C, Ji L, Tang K, Zhou M (2011) Feature selection and parameter optimization for support vector machines: A new approach based on genetic algorithm with feature chromosomes. Expert Systems with Applications 38:5197\u20135204","journal-title":"Expert Systems with Applications"},{"key":"1202_CR13","doi-asserted-by":"crossref","unstructured":"Wang C, Lin Y, Liu J (2019) Feature selection for multi-label learning with missing labels. Applied Intelligence 1\u201316","DOI":"10.1007\/s10489-019-01431-6"},{"key":"1202_CR14","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1016\/j.ins.2017.09.028","volume":"422","author":"E Hancer","year":"2018","unstructured":"Hancer E, Xue B, Zhang M, Karaboga D, Akay B (2018) Pareto front feature selection based on artificial bee colony optimization. Information Sciences 422:462\u2013479","journal-title":"Information Sciences"},{"key":"1202_CR15","doi-asserted-by":"publisher","first-page":"456","DOI":"10.1016\/j.jocs.2017.07.018","volume":"25","author":"LM Abualigah","year":"2018","unstructured":"Abualigah LM, Khader AT, Hanandeh ES (2018) A new feature selection method to improve the document clustering using particle swarm optimization algorithm. Journal of Computational Science 25:456\u2013466","journal-title":"Journal of Computational Science"},{"key":"1202_CR16","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1080\/10095020.2017.1399674","volume":"21","author":"S Amini","year":"2018","unstructured":"Amini S, Homayouni S, Safari A, Darvishsefat AA (2018) Object-based classification of hyperspectral data using random forest algorithm. Geo-spatial Information Science 21:127\u2013138","journal-title":"Geo-spatial Information Science"},{"key":"1202_CR17","doi-asserted-by":"crossref","unstructured":"Abualigah L (2020) Multi-verse optimizer algorithm: a comprehensive survey of its results, variants, and applications. Neural Computing and Applications 1\u201321","DOI":"10.1007\/s00521-020-04839-1"},{"key":"1202_CR18","doi-asserted-by":"publisher","first-page":"437","DOI":"10.1016\/j.asoc.2016.08.041","volume":"49","author":"AL Bolaji","year":"2016","unstructured":"Bolaji AL, Al-Betar MA, Awadallah MA, Khader AT, Abualigah LM (2016) A comprehensive review: Krill herd algorithm (kh) and its applications. Applied Soft Computing 49:437\u2013446","journal-title":"Applied Soft Computing"},{"key":"1202_CR19","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1049\/trit.2017.0019","volume":"2","author":"X Xu","year":"2017","unstructured":"Xu X, Liu Y (2017) Recent advances in intelligent robotic systems. CAAI Transactions on Intelligence Technology 2:141\u2013141","journal-title":"CAAI Transactions on Intelligence Technology"},{"key":"1202_CR20","doi-asserted-by":"crossref","unstructured":"Abualigah LMQ (2019) Feature Selection and Enhanced Krill Herd Algorithm for Text Document Clustering, Studies in Computational Intelligence book series, Springer","DOI":"10.1007\/978-3-030-10674-4"},{"key":"1202_CR21","doi-asserted-by":"crossref","unstructured":"Abualigah LM, Khader AT, Al-Betar MA, Alyasseri ZAA, Alomari OA, Hanandeh ES (2017) Feature selection with $$\\beta$$-hill climbing search for text clustering application. In: Information and Communication Technology (PICICT), 2017 Palestinian International Conference on, IEEE, pp 22\u201327","DOI":"10.1109\/PICICT.2017.30"},{"key":"1202_CR22","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1016\/j.jocs.2013.11.007","volume":"5","author":"KK Bharti","year":"2014","unstructured":"Bharti KK, Singh PK (2014) A three-stage unsupervised dimension reduction method for text clustering. Journal of Computational Science 5:156\u2013169","journal-title":"Journal of Computational Science"},{"key":"1202_CR23","doi-asserted-by":"crossref","unstructured":"Abualigah LM, Khader AT, Al-Betar MA, Awadallah MA (2016) A krill herd algorithm for efficient text documents clustering. In: Computer Applications & Industrial Electronics (ISCAIE), 2016 IEEE Symposium on, IEEE, pp 67\u201372","DOI":"10.1109\/ISCAIE.2016.7575039"},{"key":"1202_CR24","doi-asserted-by":"crossref","unstructured":"Bharti KK, Singh P (2014) Chaotic artificial bee colony for text clustering. In: 2014 Fourth International Conference of Emerging Applications of Information Technology, IEEE, 2014, pp 337\u2013343","DOI":"10.1109\/EAIT.2014.48"},{"key":"1202_CR25","doi-asserted-by":"crossref","unstructured":"Bharti KK, Singh PK (2016) Opposition chaotic fitness mutation based adaptive inertia weight bpso for feature selection in text clustering. Applied Soft Computing","DOI":"10.1016\/j.asoc.2016.01.019"},{"key":"1202_CR26","doi-asserted-by":"publisher","first-page":"190","DOI":"10.1016\/j.future.2017.12.005","volume":"82","author":"N Kushwaha","year":"2018","unstructured":"Kushwaha N, Pant M (2018) Link based bpso for feature selection in big data text clustering. Future Generation Computer Systems 82:190\u2013199","journal-title":"Future Generation Computer Systems"},{"key":"1202_CR27","doi-asserted-by":"crossref","unstructured":"Abualigah LM, Khader AT, Hanandeh ES (2018) A novel weighting scheme applied to improve the text document clustering techniques. In: Innovative Computing, Optimization and Its Applications, Springer, pp 305\u2013320","DOI":"10.1007\/978-3-319-66984-7_18"},{"key":"1202_CR28","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.eswa.2017.05.002","volume":"84","author":"LM Abualigah","year":"2017","unstructured":"Abualigah LM, Khader AT, Al-Betar MA, Alomari OA (2017) Text feature selection with a robust weight scheme and dynamic dimension reduction to text document clustering. Expert Systems with Applications 84:24\u201336","journal-title":"Expert Systems with Applications"},{"key":"1202_CR29","doi-asserted-by":"crossref","unstructured":"Morrison RW, Jong KAD (2002) Measurement of population diversity. In: Selected Papers from the 5th European Conference on Artificial Evolution, Springer-Verlag, London, UK, UK, 2002, pp. 31\u201341. http:\/\/dl.acm.org\/citation.cfm?id=647456.727749","DOI":"10.1007\/3-540-46033-0_3"},{"key":"1202_CR30","doi-asserted-by":"publisher","first-page":"76","DOI":"10.3390\/en11010076","volume":"11","author":"G Chen","year":"2018","unstructured":"Chen G, Lu Z, Zhang Z (2018) Improved krill herd algorithm with novel constraint handling method for solving optimal power flow problems. Energies 11:76","journal-title":"Energies"},{"key":"1202_CR31","doi-asserted-by":"publisher","first-page":"3177","DOI":"10.1016\/j.eswa.2009.09.064","volume":"37","author":"\u0130 Babaoglu","year":"2010","unstructured":"Babaoglu \u0130, Findik O, \u00dclker E (2010) A comparison of feature selection models utilizing binary particle swarm optimization and genetic algorithm in determining coronary artery disease using support vector machine. Expert Systems with Applications 37:3177\u20133183","journal-title":"Expert Systems with Applications"},{"key":"1202_CR32","doi-asserted-by":"publisher","first-page":"4831","DOI":"10.1016\/j.cnsns.2012.05.010","volume":"17","author":"AH Gandomi","year":"2012","unstructured":"Gandomi AH, Alavi AH (2012) Krill herd: a new bio-inspired optimization algorithm. Communications in Nonlinear Science and Numerical Simulation 17:4831\u20134845","journal-title":"Communications in Nonlinear Science and Numerical Simulation"},{"key":"1202_CR33","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1016\/j.future.2018.03.020","volume":"85","author":"M Abdel-Basset","year":"2018","unstructured":"Abdel-Basset M, Manogaran G, El-Shahat D, Mirjalili S (2018) A hybrid whale optimization algorithm based on local search strategy for the permutation flow shop scheduling problem. Future Generation Computer Systems 85:129\u2013145","journal-title":"Future Generation Computer Systems"},{"key":"1202_CR34","doi-asserted-by":"crossref","unstructured":"Abualigah LM, Khader AT, Hanandeh ES (2019) Modified krill herd algorithm for global numerical optimization problems. In: Advances in Nature-Inspired Computing and Applications, Springer, pp 205\u2013221","DOI":"10.1007\/978-3-319-96451-5_9"},{"key":"1202_CR35","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1016\/j.engappai.2018.05.003","volume":"73","author":"LM Abualigah","year":"2018","unstructured":"Abualigah LM, Khader AT, Hanandeh ES (2018) A combination of objective functions and hybrid krill herd algorithm for text document clustering analysis. Engineering Applications of Artificial Intelligence 73:111\u2013125","journal-title":"Engineering Applications of Artificial Intelligence"},{"key":"1202_CR36","doi-asserted-by":"crossref","unstructured":"Abualigah LM, Khader AT, Al-Betar MA (2016) Unsupervised feature selection technique based on genetic algorithm for improving the text clustering, in: Computer Science and Information Technology (CSIT), 2016 7th International Conference on, IEEE, pp 1\u20136","DOI":"10.1109\/CSIT.2016.7549453"},{"key":"1202_CR37","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/j.asoc.2018.11.047","volume":"76","author":"Q Tu","year":"2019","unstructured":"Tu Q, Chen X, Liu X (2019) Multi-strategy ensemble grey wolf optimizer and its application to feature selection. Applied Soft Computing 76:16\u201330","journal-title":"Applied Soft Computing"},{"key":"1202_CR38","doi-asserted-by":"crossref","unstructured":"Abualigah L, Diabat A (2020) A novel hybrid antlion optimization algorithm for multi-objective task scheduling problems in cloud computing environments. Cluster Computing 1\u201319","DOI":"10.1007\/s10586-020-03075-5"},{"key":"1202_CR39","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/j.neucom.2015.02.048","volume":"159","author":"R Forsati","year":"2015","unstructured":"Forsati R, Keikha A, Shamsfard M (2015) An improved bee colony optimization algorithm with an application to document clustering. Neurocomputing 159:9\u201326","journal-title":"Neurocomputing"},{"key":"1202_CR40","doi-asserted-by":"publisher","first-page":"3105","DOI":"10.1016\/j.eswa.2014.11.038","volume":"42","author":"KK Bharti","year":"2015","unstructured":"Bharti KK, Singh PK (2015) Hybrid dimension reduction by integrating feature selection with feature extraction method for text clustering. Expert Systems with Applications 42:3105\u20133114","journal-title":"Expert Systems with Applications"},{"key":"1202_CR41","doi-asserted-by":"publisher","first-page":"1113","DOI":"10.1007\/s00500-014-1571-7","volume":"20","author":"KK Bharti","year":"2016","unstructured":"Bharti KK, Singh PK (2016) Chaotic gradient artificial bee colony for text clustering. Soft Computing 20:1113\u20131126","journal-title":"Soft Computing"},{"key":"1202_CR42","unstructured":"Rose JD (2016) An efficient association rule based hierarchical algorithm for text clustering, Int J Adv Engg Tech\/Vol. VII\/Issue I\/Jan.-March 751 (2016) 753"},{"key":"1202_CR43","unstructured":"Abualigah LM, Sawaie AM, Khader AT, Rashaideh H, Al-Betar MA, Shehab M (2017a) $$\\beta$$-hill climbing technique for the text document clustering. New Trends in Information Technology 60"},{"key":"1202_CR44","doi-asserted-by":"crossref","unstructured":"Abualigah LM, Khader AT, AlBetar MA, Hanandeh ES (2017b) Unsupervised text feature selection technique based on particle swarm optimization algorithm for improving the text clustering. In: Eai International Conference on Computer Science and Engineering","DOI":"10.4108\/eai.27-2-2017.152282"},{"key":"1202_CR45","doi-asserted-by":"crossref","unstructured":"Kushwaha N, Pant M (2017) Link based bpso for feature selection in big data text clustering. Future Generation Computer Systems","DOI":"10.1016\/j.future.2017.12.005"},{"key":"1202_CR46","doi-asserted-by":"publisher","first-page":"1251","DOI":"10.3906\/elk-1508-31","volume":"25","author":"M Mirhosseini","year":"2017","unstructured":"Mirhosseini M (2017) A clustering approach using a combination of gravitational search algorithm and k-harmonic means and its application in text document clustering. Turkish Journal of Electrical Engineering & Computer Sciences 25:1251\u20131262","journal-title":"Turkish Journal of Electrical Engineering & Computer Sciences"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-020-01202-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-020-01202-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-020-01202-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,30]],"date-time":"2021-09-30T01:29:25Z","timestamp":1632965365000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-020-01202-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,30]]},"references-count":46,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2021,3]]}},"alternative-id":["1202"],"URL":"https:\/\/doi.org\/10.1007\/s13042-020-01202-7","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,9,30]]},"assertion":[{"value":"12 December 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 September 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 September 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interest"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Informed consent was obtained from all individual participants included in the study.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}]}}