{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,9]],"date-time":"2025-09-09T21:46:25Z","timestamp":1757454385124,"version":"3.40.3"},"publisher-location":"Cham","reference-count":41,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031126697"},{"type":"electronic","value":"9783031126703"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-12670-3_19","type":"book-chapter","created":{"date-parts":[[2022,7,25]],"date-time":"2022-07-25T15:07:54Z","timestamp":1658761674000},"page":"219-233","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Q-VIPER: Quantitative Vertical Bitwise Algorithm to Mine Frequent Patterns"],"prefix":"10.1007","author":[{"given":"Thomas J.","family":"Czubryt","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7541-9127","authenticated-orcid":false,"given":"Carson K.","family":"Leung","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adam G. M.","family":"Pazdor","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,7,26]]},"reference":[{"key":"19_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1007\/978-3-319-98539-8_25","volume-title":"Big Data Analytics and Knowledge Discovery","author":"P Bemarisika","year":"2018","unstructured":"Bemarisika, P., Totohasina, A.: ERAPN, an algorithm for extraction positive and negative association rules in big data. In: Ordonez, C., Bellatreche, L. (eds.) DaWaK 2018. LNCS, vol. 11031, pp. 329\u2013344. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-98539-8_25"},{"key":"19_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1007\/978-3-030-86534-4_6","volume-title":"Big Data Analytics and Knowledge Discovery","author":"CK Leung","year":"2021","unstructured":"Leung, C.K., Fung, D.L.X., Hoi, C.S.H.: Health analytics on COVID-19 data with few-shot learning. In: Golfarelli, M., Wrembel, R., Kotsis, G., Tjoa, A.M., Khalil, I. (eds.) DaWaK 2021. LNCS, vol. 12925, pp. 67\u201380. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-86534-4_6"},{"key":"19_CR3","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"224","DOI":"10.1007\/978-3-030-22354-0_21","volume-title":"Complex, Intelligent, and Software Intensive Systems","author":"A-RA Audu","year":"2020","unstructured":"Audu, A.-R.A., Cuzzocrea, A., Leung, C.K., MacLeod, K.A., Ohin, N.I., Pulgar-Vidal, N.C.: An intelligent predictive analytics system for transportation analytics on open data towards the development of a smart city. In: Barolli, L., Hussain, F.K., Ikeda, M. (eds.) CISIS 2019. AISC, vol. 993, pp. 224\u2013236. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-22354-0_21"},{"key":"19_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1007\/978-3-030-27520-4_3","volume-title":"Big Data Analytics and Knowledge Discovery","author":"CK Leung","year":"2019","unstructured":"Leung, C.K., Braun, P., Hoi, C.S.H., Souza, J., Cuzzocrea, A.: Urban analytics of big transportation data for supporting smart cities. In: Ordonez, C., Song, I.-Y., Anderst-Kotsis, G., Tjoa, A.M., Khalil, I. (eds.) DaWaK 2019. LNCS, vol. 11708, pp. 24\u201333. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-27520-4_3"},{"key":"19_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1007\/978-3-319-98539-8_7","volume-title":"Big Data Analytics and Knowledge Discovery","author":"CK Leung","year":"2018","unstructured":"Leung, C.K., Braun, P., Pazdor, A.G.M.: Effective classification of ground transportation modes for urban data mining in smart cities. In: Ordonez, C., Bellatreche, L. (eds.) DaWaK 2018. LNCS, vol. 11031, pp. 83\u201397. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-98539-8_7"},{"key":"19_CR6","doi-asserted-by":"crossref","unstructured":"Ahn, S., et al.: A fuzzy logic based machine learning tool for supporting big data business analytics in complex artificial intelligence environments. In: FUZZ-IEEE, pp. 1259\u20131264 (2019)","DOI":"10.1109\/FUZZ-IEEE.2019.8858791"},{"key":"19_CR7","doi-asserted-by":"crossref","unstructured":"Morris, K.J., et al.: Token-based adaptive time-series prediction by ensembling linear and non-linear estimators: a machine learning approach for predictive analytics on big stock data. In: IEEE ICMLA, pp. 1486\u20131491 (2018)","DOI":"10.1109\/ICMLA.2018.00242"},{"key":"19_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1007\/978-3-319-64283-3_10","volume-title":"Big Data Analytics and Knowledge Discovery","author":"P Braun","year":"2017","unstructured":"Braun, P., Cuzzocrea, A., Jiang, F., Leung, C.K.-S., Pazdor, A.G.M.: MapReduce-based complex big data analytics over uncertain and imprecise social networks. In: Bellatreche, L., Chakravarthy, S. (eds.) DaWaK 2017. LNCS, vol. 10440, pp. 130\u2013145. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-64283-3_10"},{"key":"19_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"308","DOI":"10.1007\/978-3-319-10160-6_28","volume-title":"Data Warehousing and Knowledge Discovery","author":"F Jiang","year":"2014","unstructured":"Jiang, F., Leung, C.K.-S.: Mining interesting \u201cfollowing\u201d patterns from social networks. In: Bellatreche, L., Mohania, M.K. (eds.) DaWaK 2014. LNCS, vol. 8646, pp. 308\u2013319. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10160-6_28"},{"key":"19_CR10","doi-asserted-by":"publisher","unstructured":"Leung, C.K.: Mathematical model for propagation of influence in a social network. In: Alhajj, R., Rokne, J. (eds.) Encyclopedia of Social Network Analysis and Mining, 2nd edn., pp. 1261\u20131269. Springer, New York, NY (2018). https:\/\/doi.org\/10.1007\/978-1-4939-7131-2_110201","DOI":"10.1007\/978-1-4939-7131-2_110201"},{"issue":"15","key":"19_CR11","doi-asserted-by":"publisher","first-page":"3994","DOI":"10.1002\/cpe.3773","volume":"28","author":"CK Leung","year":"2016","unstructured":"Leung, C.K., et al.: Parallel social network mining for interesting \u2018following\u2019 patterns. Concurr. Comput. Pract. Exp. 28(15), 3994\u20134012 (2016)","journal-title":"Concurr. Comput. Pract. Exp."},{"key":"19_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"502","DOI":"10.1007\/978-3-642-32600-4_38","volume-title":"Database and Expert Systems Applications","author":"NR Arora","year":"2012","unstructured":"Arora, N.R., Lee, W., Leung, C.K.-S., Kim, J., Kumar, H.: Efficient fuzzy ranking for keyword search on graphs. In: Liddle, S.W., Schewe, K.-D., Tjoa, A.M., Zhou, X. (eds.) DEXA 2012, Part I. LNCS, vol. 7446, pp. 502\u2013510. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-32600-4_38"},{"key":"19_CR13","doi-asserted-by":"crossref","unstructured":"Eom, C.S., et al.: Effective privacy preserving data publishing by vectorization. Inf. Sci. 527, 311\u2013328 (2020)","DOI":"10.1016\/j.ins.2019.09.035"},{"key":"19_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1007\/978-3-030-59051-2_28","volume-title":"Database and Expert Systems Applications","author":"AM Olawoyin","year":"2020","unstructured":"Olawoyin, A.M., Leung, C.K., Choudhury, R.: Privacy-preserving spatio-temporal patient data publishing. In: Hartmann, S., K\u00fcng, J., Kotsis, G., Tjoa, A.M., Khalil, I. (eds.) DEXA 2020, Part II. LNCS, vol. 12392, pp. 407\u2013416. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-59051-2_28"},{"key":"19_CR15","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1007\/978-3-319-22729-0_10","volume-title":"Big Data Analytics and Knowledge Discovery","author":"CK-S Leung","year":"2015","unstructured":"Leung, C.K.-S., Jiang, F.: Big data analytics of social networks for the discovery of \u201cfollowing\u201d patterns. In: Madria, S., Hara, T. (eds.) DaWaK 2015. LNCS, vol. 9263, pp. 123\u2013135. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-22729-0_10"},{"key":"19_CR16","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"669","DOI":"10.1007\/978-3-030-44041-1_59","volume-title":"Advanced Information Networking and Applications","author":"J Souza","year":"2020","unstructured":"Souza, J., Leung, C.K., Cuzzocrea, A.: An innovative big data predictive analytics framework over hybrid big data sources with an application for disease analytics. In: Barolli, L., Amato, F., Moscato, F., Enokido, T., Takizawa, M. (eds.) AINA 2020. AISC, vol. 1151, pp. 669\u2013680. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-44041-1_59"},{"key":"19_CR17","doi-asserted-by":"publisher","unstructured":"Couronne, C., Koptelov, M., Zimmermann, A.: PrePeP: a light-weight, extensible tool for predicting frequent hitters. In: Dong, Y., Ifrim, G., Mladenic, D., Saunders, C., Van Hoecke, S. (eds.) ECML PKDD 2020, Part V. Applied Data Science and Demo Track. LNCS, vol. 12461. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-67670-4_41","DOI":"10.1007\/978-3-030-67670-4_41"},{"key":"19_CR18","doi-asserted-by":"publisher","unstructured":"Fischer, J., Vreeken, J.: Sets of robust rules, and howto find them. In: Brefeld, U., Fromont, E., Hotho, A., Knobbe, A., Maathuis, M., Robardet, C. (eds.) ECML PKDD 2019. LNCS, vol. 11906. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-46150-8_3","DOI":"10.1007\/978-3-030-46150-8_3"},{"key":"19_CR19","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1007\/978-3-642-32584-7_24","volume-title":"Data Warehousing and Knowledge Discovery","author":"CK-S Leung","year":"2012","unstructured":"Leung, C.K.-S., Tanbeer, S.K.: Mining popular patterns from transactional databases. In: Cuzzocrea, A., Dayal, U. (eds.) DaWaK 2012. LNCS, vol. 7448, pp. 291\u2013302. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-32584-7_24"},{"key":"19_CR20","doi-asserted-by":"publisher","unstructured":"Seiffarth, F., Horvath, T., Wrobel, S.: Maximal closed set and half-space separations in finite closure systems. In: Brefeld, U., Fromont, E., Hotho, A., Knobbe, A., Maathuis, M., Robardet, C. (eds.) Machine ECML PKDD 2019, Part I. LNCS, vol. 11906. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-46150-8_2","DOI":"10.1007\/978-3-030-46150-8_2"},{"key":"19_CR21","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-030-75765-6_1","volume-title":"Advances in Knowledge Discovery and Data Mining","author":"MT Alam","year":"2021","unstructured":"Alam, M.T., Ahmed, C.F., Samiullah, M., Leung, C.K.: Mining frequent patterns from hypergraph databases. In: Karlapalem, K., et al. (eds.) PAKDD 2021, Part II. LNCS (LNAI), vol. 12713, pp. 3\u201315. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-75765-6_1"},{"key":"19_CR22","doi-asserted-by":"crossref","unstructured":"Chowdhury, M.E.S., et al.: A new approach for mining correlated frequent subgraphs. ACM Trans. Manag. Inf. Syst. 13(1), 9:1\u20139:28 (2022)","DOI":"10.1145\/3473042"},{"key":"19_CR23","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"335","DOI":"10.1007\/978-3-642-21852-1_40","volume-title":"Foundations of Augmented Cognition. Directing the Future of Adaptive Systems","author":"CK-S Leung","year":"2011","unstructured":"Leung, C.K.-S., Carmichael, C.L., Teh, E.W.: Visual analytics of social networks: mining and visualizing co-authorship networks. In: Schmorrow, D.D., Fidopiastis, C.M. (eds.) FAC 2011. LNCS (LNAI), vol. 6780, pp. 335\u2013345. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-21852-1_40"},{"key":"19_CR24","doi-asserted-by":"publisher","unstructured":"Cuzzocrea, A., Jiang, F., Leung, C.K., Liu, D., Peddle, A., Tanbeer, S.K.: Mining popular patterns: a novel mining problem and its application to static transactional databases and dynamic data streams. In: Hameurlain, A., K\u00fcng, J., Wagner, R., Cuzzocrea, A., Dayal, U. (eds) Transactions on Large-Scale Data- and Knowledge-Centered Systems XXI. LNCS, vol. 9260. Springer, Heidelberg (2015). https:\/\/doi.org\/10.1007\/978-3-662-47804-2_6","DOI":"10.1007\/978-3-662-47804-2_6"},{"key":"19_CR25","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1007\/978-3-642-40131-2_18","volume-title":"Data Warehousing and Knowledge Discovery","author":"F Jiang","year":"2013","unstructured":"Jiang, F., Leung, C.K.-S.: Stream mining of frequent patterns from delayed batches of uncertain data. In: Bellatreche, L., Mohania, M.K. (eds.) DaWaK 2013. LNCS, vol. 8057, pp. 209\u2013221. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-40131-2_18"},{"key":"19_CR26","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"252","DOI":"10.1007\/978-3-642-23544-3_19","volume-title":"Data Warehousing and Knowledge Discovery","author":"CK-S Leung","year":"2011","unstructured":"Leung, C.K.-S., Jiang, F.: Frequent pattern mining from time-fading streams of uncertain data. In: Cuzzocrea, A., Dayal, U. (eds.) DaWaK 2011. LNCS, vol. 6862, pp. 252\u2013264. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-23544-3_19"},{"key":"19_CR27","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1007\/978-3-319-22729-0_5","volume-title":"Big Data Analytics and Knowledge Discovery","author":"CK-S Leung","year":"2015","unstructured":"Leung, C.K.-S., MacKinnon, R.K.: Balancing tree size and accuracy in fast mining of uncertain frequent patterns. In: Madria, S., Hara, T. (eds.) DaWaK 2015. LNCS, vol. 9263, pp. 57\u201369. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-22729-0_5"},{"key":"19_CR28","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1007\/978-3-319-10160-6_11","volume-title":"Data Warehousing and Knowledge Discovery","author":"C-S Leung","year":"2014","unstructured":"Leung, C.-S., MacKinnon, R.K.: BLIMP: a compact tree structure for uncertain frequent pattern mining. In: Bellatreche, L., Mohania, M.K. (eds.) DaWaK 2014. LNCS, vol. 8646, pp. 115\u2013123. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10160-6_11"},{"key":"19_CR29","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1007\/978-3-030-75765-6_3","volume-title":"Advances in Knowledge Discovery and Data Mining","author":"KK Roy","year":"2021","unstructured":"Roy, K.K., Moon, M.H.H., Rahman, M.M., Ahmed, C.F., Leung, C.K.: Mining sequential patterns in uncertain databases using hierarchical index structure. In: Karlapalem, K., et al. (eds.) PAKDD 2021, Part II. LNCS (LNAI), vol. 12713, pp. 29\u201341. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-75765-6_3"},{"key":"19_CR30","doi-asserted-by":"publisher","unstructured":"Ishita, S.Z., Ahmed, C.F., Leung, C.K.: New approaches for mining regular high utility sequential patterns. Appl. Intell. 52,\u00a03781\u20133806\u00a0(2022). https:\/\/doi.org\/10.1007\/s10489-021-02536-7","DOI":"10.1007\/s10489-021-02536-7"},{"key":"19_CR31","doi-asserted-by":"crossref","unstructured":"Nguyen, H., et al.: Mining frequent weighted utility itemsets in hierarchical quantitative databases. Knowl. Based Syst. 237, 107709:1\u2013107709:13 (2022)","DOI":"10.1016\/j.knosys.2021.107709"},{"issue":"10","key":"19_CR32","doi-asserted-by":"publisher","first-page":"6785","DOI":"10.1007\/s10489-021-02204-w","volume":"51","author":"M Nouioua","year":"2021","unstructured":"Nouioua, M., et al.: FHUQI-Miner: fast high utility quantitative itemset mining. Appl. Intell. 51(10), 6785\u20136809 (2021). https:\/\/doi.org\/10.1007\/s10489-021-02204-w","journal-title":"Appl. Intell."},{"key":"19_CR33","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-319-98809-2_1","volume-title":"Database and Expert Systems Applications","author":"CK Leung","year":"2018","unstructured":"Leung, C.K., Zhang, H., Souza, J., Lee, W.: Scalable vertical mining for big data analytics of frequent itemsets. In: Hartmann, S., Ma, H., Hameurlain, A., Pernul, G., Wagner, R.R. (eds.) DEXA 2018, Part I. LNCS, vol. 11029, pp. 3\u201317. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-98809-2_1"},{"issue":"3","key":"19_CR34","first-page":"372","volume":"12","author":"MJ Zaki","year":"2000","unstructured":"Zaki, M.J.: Scalable algorithms for association mining. IEEE TKDE 12(3), 372\u2013390 (2000)","journal-title":"IEEE TKDE"},{"key":"19_CR35","doi-asserted-by":"crossref","unstructured":"Zaki, M.J., Gouda, K.: Fast vertical mining using diffsets. In: ACM KDD, pp. 326\u2013335 (2003)","DOI":"10.1145\/956750.956788"},{"key":"19_CR36","doi-asserted-by":"crossref","unstructured":"Agrawal, R., et al.: Mining association rules between sets of items in large databases. In: ACM SIGMOD, pp. 207\u2013216 (1993)","DOI":"10.1145\/170036.170072"},{"key":"19_CR37","unstructured":"Agrawal, R., Srikant, R.: Fast algorithms for mining association rules. In: VLDB, pp. 487\u2013499 (1994)"},{"key":"19_CR38","doi-asserted-by":"crossref","unstructured":"Shenoy, P., et al.: Turbo-charging vertical mining of large databases. In: ACM SIGMOD, pp. 22\u201333 (2000)","DOI":"10.1145\/335191.335376"},{"issue":"1\u20134","key":"19_CR39","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1016\/j.ins.2003.05.013","volume":"166","author":"PY Hsu","year":"2004","unstructured":"Hsu, P.Y., et al.: Algorithms for mining association rules in bag databases. Inf. Sci. 166(1\u20134), 31\u201347 (2004)","journal-title":"Inf. Sci."},{"key":"19_CR40","doi-asserted-by":"crossref","unstructured":"Srikant, R., Agrawal, R.: Mining quantitative association rules in large relational tables. In: ACM SIGMOD, pp. 1\u201312 (1996)","DOI":"10.1145\/235968.233311"},{"key":"19_CR41","unstructured":"Dua, D., Graff, C.: UCI Machine Learning Repository. http:\/\/archive.ics.uci.edu\/ml"}],"container-title":["Lecture Notes in Computer Science","Big Data Analytics and Knowledge Discovery"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-12670-3_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T16:31:09Z","timestamp":1710261069000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-12670-3_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031126697","9783031126703"],"references-count":41,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-12670-3_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"26 July 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DaWaK","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Big Data Analytics and Knowledge Discovery","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vienna","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Austria","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 August 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 August 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dawak2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.dexa.org\/dawak2022","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"57","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"12","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"12","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"21% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}