Skip to main content

Information System Function-Data Architecture Planning Based on Subspace Partition

  • Conference paper
  • First Online:
LISS 2022 (LISS 2022)

Part of the book series: Lecture Notes in Operations Research ((LNOR))

  • 259 Accesses

Abstract

Under the background of big data, the development of enterprise business and the growth of data lead to the characteristics of enterprise information system with complex business functions, large amount of data, and sparse connection between functions and data. Therefore, dividing the information system structure based on the link between functions and data can effectively improve the construction and operation efficiency of enterprise information systems and facilitate system maintenance and management. However, the traditional information system planning method only focuses on the planning of the functions, and cannot plan a reasonable data structure at the same time. In order to solve the above problems, this study proposes A Information System Function-Data Architecture Planning Method that can simultaneously complete the information system function-data system planning. It takes the Function-Data Subspace Partition Algorithm as the core, and realizes the information system structure partition from the perspective of function and data at the same time.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+
from €39.99 /Month
  • Starting from 10 chapters or articles per month
  • Access and download chapters and articles from more than 300k books and 2,500 journals
  • Cancel anytime
View plans

Buy Now

Chapter
EUR 29.95
Price includes VAT (Germany)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
EUR 149.79
Price includes VAT (Germany)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
EUR 192.59
Price includes VAT (Germany)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
EUR 192.59
Price includes VAT (Germany)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

') var buybox = document.querySelector("[data-id=id_"+ timestamp +"]").parentNode var buyingOptions = buybox.querySelectorAll(".buying-option") ;[].slice.call(buyingOptions).forEach(initCollapsibles) var buyboxMaxSingleColumnWidth = 480 function initCollapsibles(subscription, index) { var toggle = subscription.querySelector(".buying-option-price") subscription.classList.remove("expanded") var form = subscription.querySelector(".buying-option-form") var priceInfo = subscription.querySelector(".price-info") var buyingOption = toggle.parentElement if (toggle && form && priceInfo) { toggle.setAttribute("role", "button") toggle.setAttribute("tabindex", "0") toggle.addEventListener("click", function (event) { var expandedBuyingOptions = buybox.querySelectorAll(".buying-option.expanded") var buyboxWidth = buybox.offsetWidth ;[].slice.call(expandedBuyingOptions).forEach(function(option) { if (buyboxWidth buyboxMaxSingleColumnWidth) { toggle.click() } else { if (index === 0) { toggle.click() } else { toggle.setAttribute("aria-expanded", "false") form.hidden = "hidden" priceInfo.hidden = "hidden" } } }) } initialStateOpen() if (window.buyboxInitialised) return window.buyboxInitialised = true initKeyControls() })()

Institutional subscriptions

Similar content being viewed by others

References

  1. Davis, B.G.: Management Information Systems: Conceptual Foundations, Structure, and Development-2/E. McGraw-Hill, Inc. McGraw-Hill, Inc. (1974)

    Google Scholar 

  2. IBM, Business System Planning—Information System Planning Guide, 3rd edn (1981)

    Google Scholar 

  3. Inmon, W.H.: Building the Data Warehouse. John Wiley & Sons, Inc. (1992)

    Google Scholar 

  4. Sun, Y., Han, J., Zhao, P., et al.: RankClus: integrating clustering with ranking for heterogeneous information network analysis. In: Proceedings of the 12th International Conference on Extending Data-base Technology: Advances in Database Technology. ACM, NewYork, pp. 565–576 (2009)

    Google Scholar 

  5. Sun, Y., Han, J.: Mining heterogeneous information networks: principles and methodologies. ACM SIG-KDD Explor. Newsl. 14(2), 439–473 (2012)

    Google Scholar 

  6. Han , J.: Mining Heterogeneous Information Networks by Exploring the Power of Links. Springer, Berlin, Heidelberg (2009)

    Google Scholar 

  7. Sun, Y., Han, J., Yan, X., et al.: PathSim: meta path-based top K similarity search in heterogeneous information networks. Proceed. Vldb Endowment 4(11), 992–1003 (2011)

    Article  Google Scholar 

  8. Shi, C., Zhang, Z., Luo, P., et al.: Semantic path based personal-ized recommendation on weighted heterogeneous information networks. ACM Int. Conf. Inf. Knowl. Manage. 453–462 (2015)

    Google Scholar 

  9. Huang, Z., Zheng, Y., Cheng, R., et al.: Meta structure: computing relevance in large heterogeneous information networks. In: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. CM, pp. 1595–1604 (2016)

    Google Scholar 

  10. Fang, Y., Lin, W., Zheng, V.W., et al.: Semantic proximity search on graphs with meta graph-based learning. In: IEEE,International Conference on Data Engineering. IEEE Computer Society, pp. 277–288 (2016)

    Google Scholar 

  11. Shi, C., Li, Y.T., Zhang, J.W., et al.: A survey of heterogeneous information network analysis. IEEE Trans. Knowl. Data Eng. 29(1), 17–37 (2017)

    Article  Google Scholar 

  12. Zhou, Z.N.: A system analysis method—U/C matrix. Appl. Res. Comput. 012(004), 41–42 (1995)

    Google Scholar 

  13. Agrawal, R.: Mining association rules between sets of items in large database. In: Proceedings of the 1993 ACM SIGMOD Conference, Washington DC, USA (1993)

    Google Scholar 

  14. Wu, H., Wang, Y.J., Wang, Z., et al.: Two-phase collaborative filtering algorithm based on co-clustering. J. Softw. 21(5), 1042–1054 (2010)

    Article  Google Scholar 

  15. Zhang, T., Ramakrishnan, R., Livny, M.: BIRCH: a new data clustering algorithm and its applications. J. Data Min. Knowl. Discov. 1(2), 141–182 (1997)

    Article  Google Scholar 

  16. Xue, H.C.: Management Information Systems, 2nd edn. Tsinghua University Press (1993)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xuedong Gao .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Huo, Y., Gao, X., Wang, A. (2023). Information System Function-Data Architecture Planning Based on Subspace Partition. In: Shang, X., Fu, X., Ma, Y., Gong, D., Zhang, J. (eds) LISS 2022. LISS 2022. Lecture Notes in Operations Research. Springer, Singapore. https://doi.org/10.1007/978-981-99-2625-1_6

Download citation

Publish with us

Policies and ethics