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Tytuł artykułu

Design of data analysis systems for business process automation

Treść / Zawartość
Identyfikatory
Warianty tytułu
PL
Projektowanie systemów analizy danych do automatyzacji procesów biznesowych
Języki publikacji
EN
Abstrakty
EN
The paper deals with the design of data analysis systems for business process automation. The main goal of the project is to develop an innovative system for analyzing multisource data, business data mining processes, and as a result the creation and sharing of new improved procedures and solutions.
PL
Artykuł dotyczy projektowania systemów analizy danych do automatyzacji procesów biznesowych. Głównym celem projektu jest opracowanie innowacyjnego systemu do analizy danych wieloźródłowych, procesów eksploracji danych biznesowych, a co za tym idzie tworzenie i udostępnianie nowych ulepszonych procedur i rozwiązań.
Rocznik
Strony
43--46
Opis fizyczny
Bibliogr. 22 poz., rys., tab.
Twórcy
autor
  • Research and Development Center, Netrix S.A., Lublin
  • University of Economics and Innovation in Lublin
autor
  • Lublin University of Technology, Faculty of Management, Department of Organization of Enterprise
  • Lublin University of Technology, Faculty of Management, Department of Organization of Enterprise
autor
  • Research and Development Center, Netrix S.A., Lublin
Bibliografia
  • [1] Baker A.M., Donthu N., Kumar V.: Investigating how word-ofmouth conversations about brands influence purchase and retransmission intentions. Journal of Marketing Research 53(2)/2016, 225–239.
  • [2] Bonabeau E.: Agent-based modeling: Methods and techniques for simulating human systems. Proceedings of the National Academy of Sciences 99(3)/2002, 7280–7287.
  • [3] Borshchev A., Filippov A.: From system dynamics and discrete event to practical agent based modeling: reasons, techniques, tools. Proceedings of the 22nd international conference of the system dynamics society 22. Citeseer, 2004.
  • [4] Cearley D.W., Burke B., Searle S., Walker M. J.: Top 10 strategic technology trends for 2018. https://www.gartner.com/doc/3811368/top–strategic-technology-trends
  • [5] Chang R. M., Kauffman R. J., Kwon Y.: Understanding the paradigm shift to computational social science in the presence of big data 63/2014, 67–80.
  • [6] Demirkan H., Delen D.: Leveraging the capabilities of service oriented decision support systems. Putting analytics and big data in cloud 55(1)/2013, 412–421.
  • [7] Huang J.-H., Hsiao T.-T., Chen Y.-F.: The effects of electronic word of mouth on product judgment and choice: The moderating role of the sense of virtual community. Journal of Applied Social Psychology 42(9)/2012, 2326–2347.
  • [8] Hudson S., Huang L., Roth M.S., Madden T.J.: The influence of social media interactions on consumer–brand relationships: A three country study of brand perceptions and marketing behaviors. International Journal of Research in Marketing 33(1)/2016, 27–41.
  • [9] Jager W.: Simulating consumer behaviour: a perspective. Rapport in het kort, 2006.
  • [10] Krizanová A., Stefániková L.: Importance of the brand for consumer purchasing decision in the slovak republic. Verslo Sistemos ir Ekonomika 2(2)/2012.
  • [11] Li F., Du T.C.: The effectiveness of word of mouth in offline and online social networks. Expert Systems with Applications 88/2017, 338–351.
  • [12] Lien C.-H., Wen M.-J., Huang L.-C., Wu K.-L.: Online hotel booking: The effects of brand image, price, trust and value on purchase intentions. Asia Pacific Management Review 20(4)/2015, 210–218.
  • [13] Liu C., Du W.-B., Wang W.-X.: Particle swarm optimization with scale-free interactions PloS one, 9(5)/2014, e97822.
  • [14] López M., Sicilia M.: Determinants of e-wom influence: the role of consumers’ internet experience. Journal of theoretical and applied electronic commerce research 9(1)/2014, 28–43.
  • [15] Lu J., Yang X., Zhang G.: Support vector machine-based multisource multiattribute information integration for situation assessment. Expert Systems with Applications 34(2)/2008, 1333–1340.
  • [16] Ma Y., Zeng Y., Ren X., Zhong N.: User interests modeling based on multisource personal information fusion and semantic reasoning. International Conference on Active Media Technology, Springer, 2011, 195–205.
  • [17] Marr B.: Really big data at walmart: Real-time insights from their 40+ petabytedata cloud. https://www.forbes.com/sites/bernardmarr/2017/01/23/reallybigdata-at-walmart-real-time-insights-from-their-40-petabyte-data-cloud
  • [18] Pan A., Choi T.-M.: An agent-based negotiation model on price and deliverydate in a fashion supply chain 242(2)/2014, 529–557.
  • [19] Polakowski K., Filipowicz S., Sikora J., Rymarczyk T.: Tomography Technology Application for Workflows of Gases Monitoring in The Automotive Systems. Przegląd Elektrotechniczny 84(12)/2008, 227–229.
  • [20] Pöyry E., Parvinen P., Salo J., Blakaj H., Tiainen O.: Online information search and utilization of electronic word-of-mouth. Proceedings of the 13th International Conference on Electronic Commerce ACM 2011, 2.
  • [21] Wilensky U.: Netlogo. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston.
  • [22] Yan Q., Wu S., Wang L., Wu P., Chen H., Wei G.: E-wom from e-commerce websites and social media: Which will consumers adopt? Electronic Commerce Research and Applications 17/2016, 62–73.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b958ce49-d8b6-49c1-bd45-531f68c04444
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