IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v53y2009i7p2485-2499.html
   My bibliography  Save this article

Maintenance of fast updated frequent pattern trees for record deletion

Author

Listed:
  • Hong, Tzung-Pei
  • Lin, Chun-Wei
  • Wu, Yu-Lung

Abstract

The Frequent-Pattern-tree (FP tree) is an efficient data structure for association-rule mining without generation of candidate itemsets. It was used to represent a database into a tree structure which stored only frequent items. It, however, needed to process all transactions in a batch way. In the past, Hong etal. thus proposed an efficient incremental mining algorithm for handling newly inserted transactions. In addition to record insertion, record deletion from databases is also commonly seen in real-applications. In this paper, we thus attempt to modify the FP-tree construction algorithm for efficiently handling deletion of records. A fast updated FP-tree (FUFP-tree) structure is used, which makes the tree update process become easier. An FUFP-tree maintenance algorithm for the deletion of records is also proposed for reducing the execution time in reconstructing the tree when records are deleted. Experimental results also show that the proposed FUFP-tree maintenance algorithm for deletion of records runs faster than the batch FP-tree construction algorithm for handling deleted records and generates nearly the same tree structure as the FP-tree algorithm. The proposed approach can thus achieve a good trade-off between execution time and tree complexity.

Suggested Citation

  • Hong, Tzung-Pei & Lin, Chun-Wei & Wu, Yu-Lung, 2009. "Maintenance of fast updated frequent pattern trees for record deletion," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2485-2499, May.
  • Handle: RePEc:eee:csdana:v:53:y:2009:i:7:p:2485-2499
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(09)00027-9
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:53:y:2009:i:7:p:2485-2499. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.