東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Frequent pattern mining without cand...

Cheung, William.

FindBook

Google Book

Amazon

博客來

Frequent pattern mining without candidate generation or support constraint.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Frequent pattern mining without candidate generation or support constraint./
作者:	Cheung, William.
面頁冊數:	106 p.
附註:	Source: Masters Abstracts International, Volume: 42-02, page: 0612.
Contained By:	Masters Abstracts International42-02.
標題:	Computer Science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MQ82261
ISBN:	0612822613

Frequent pattern mining without candidate generation or support constraint.
Cheung, William.

Frequent pattern mining without candidate generation or support constraint. - 106 p.

Source: Masters Abstracts International, Volume: 42-02, page: 0612.

Thesis (M.Sc.)--University of Alberta (Canada), 2003.

Mining for frequent patterns in transactional databases has been studied for more than a decade. Many algorithms have been developed to mine static databases. There are a few incremental algorithms, FUP2 and SWF, that allow both addition and deletion of transactions. However, they are not efficient because they have to rescan the whole dataset at least once. They are not suitable in real time situations where transactions are added or deleted constantly and frequent patterns mining could be required at any time.

ISBN: 0612822613Subjects--Topical Terms:

626642
Computer Science.

Frequent pattern mining without candidate generation or support constraint.
LDR:01755nmm 2200277 4500 001 1861463
005 20041111121802.5
008 130614s2003 eng d
020 $a 0612822613
035 $a (UnM)AAIMQ82261
035 $a AAIMQ82261
040 $a UnM $c UnM
100 1 $a Cheung, William. $3 1949062
245 1 0 $a Frequent pattern mining without candidate generation or support constraint.
300 $a 106 p.
500 $a Source: Masters Abstracts International, Volume: 42-02, page: 0612.
500 $a Adviser: Osmar Zaiane.
502 $a Thesis (M.Sc.)--University of Alberta (Canada), 2003.
520 $a Mining for frequent patterns in transactional databases has been studied for more than a decade. Many algorithms have been developed to mine static databases. There are a few incremental algorithms, FUP2 and SWF, that allow both addition and deletion of transactions. However, they are not efficient because they have to rescan the whole dataset at least once. They are not suitable in real time situations where transactions are added or deleted constantly and frequent patterns mining could be required at any time.
520 $a In this thesis, we propose a novel data structure called CATS Tree. CATS Tree extends the idea of FP-Tree to improve storage compression and allow frequent pattern mining without generation of candidate itemsets. The proposed algorithms allow mining with a single pass over the database as well as addition or deletion of transactions in the finest granularity at any given time.
590 $a School code: 0351.
650 4 $a Computer Science. $3 626642
690 $a 0984
710 2 0 $a University of Alberta (Canada). $3 626651
773 0 $t Masters Abstracts International $g 42-02.
790 1 0 $a Zaiane, Osmar, $e advisor
790 $a 0351
791 $a M.Sc.
792 $a 2003
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MQ82261