Containment of partially specified tree-pattern queries in the presence of dimension graphs

2008 ◽  
Vol 18 (1) ◽  
pp. 233-254 ◽  
Author(s):  
Dimitri Theodoratos ◽  
Pawel Placek ◽  
Theodore Dalamagas ◽  
Stefanos Souldatos ◽  
Timos Sellis
Keyword(s):  
Tree Pattern

scholarly journals Monadic Datalog and Regular Tree Pattern Queries

2016 ◽  
Vol 41 (3) ◽  
pp. 1-43
Author(s):  
Filip Mazowiecki ◽  
Filip Murlak ◽  
Adam Witkowski
Keyword(s):  
Regular Tree ◽  
Tree Pattern

XMin: Minimizing Tree Pattern Queries with Minimality Guarantee

2010 ◽  
Vol 13 (3) ◽  
pp. 343-371 ◽  
Author(s):  
Ki-Hoon Lee ◽  
Kyu-Young Whang ◽  
Wook-Shin Han
Keyword(s):  
Tree Pattern

Extended XML Tree Pattern Matching: Theories and Algorithms

2011 ◽  
Vol 23 (3) ◽  
pp. 402-416 ◽  
Author(s):  
Jiaheng Lu ◽  
Tok Wang Ling ◽  
Zhifeng Bao ◽  
Chen Wang
Keyword(s):  
Pattern Matching ◽  
Tree Pattern ◽  
Tree Pattern Matching

scholarly journals On Testing Satisfiability of Tree Pattern Queries

2004 ◽  
pp. 120-131 ◽  
Author(s):  
Laks V.S. Lakshmanan ◽  
Ganesh Ramesh ◽  
Hui(wendy) Wang ◽  
Zheng(Jessica) Zhao
Keyword(s):  
Tree Pattern

XML Tree Pattern Processing

2013 ◽  
pp. 91-156 ◽  
Author(s):  
Jiaheng Lu
Keyword(s):  
Tree Pattern ◽  
Pattern Processing

Validity of Tree Pattern Queries with Respect to Schema Information

2013 ◽  
pp. 171-182 ◽  
Author(s):  
Henrik Björklund ◽  
Wim Martens ◽  
Thomas Schwentick
Keyword(s):  
Tree Pattern

Standard Fault Tree Pattern

2015 ◽  
pp. 71-80
Author(s):  
Wolfgang Freese
Keyword(s):  
Fault Tree ◽  
Tree Pattern

Multi-Label Classification Method for Multimedia Tagging

2010 ◽  
Vol 1 (3) ◽  
pp. 57-75
Author(s):  
Aiyesha Ma ◽  
Ishwar Sethi ◽  
Nilesh Patel
Keyword(s):  
New Media ◽  
Decision Tree ◽  
Pattern Classification ◽  
Classification Method ◽  
Tag Clouds ◽  
Search Results ◽  
Tree Pattern ◽  
Media Types ◽  
Media Data ◽  
Search And Retrieval

Community tagging offers valuable information for media search and retrieval, but new media items are at a disadvantage. Automated tagging may populate media items with few tags, thus enabling their inclusion into search results. In this paper, a multi-label decision tree is proposed and applied to the problem of automated tagging of media data. In addition to binary labels, the proposed Iterative Split Multi-label Decision Tree (IS-MLT) is easily extended to the problem of weighted labels (such as those depicted by tag clouds). Several datasets of differing media types show the effectiveness of the proposed method relative to other multi-label and single label classifier methods and demonstrate its scalability relative to single label approaches.Keywords: Automated Multimedia Tagging; Community Tagging; Multi-label Classification; Multi-label Decision Tree; Pattern Classification

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