Rule-Based Agricultural Knowledge Fusion in Web Information Integration

2012 ◽  
Vol 10 (1) ◽  
pp. 635-638 ◽  
Author(s):  
Xie Nengfu ◽  
Wang Wensheng ◽  
Yang Xiaorong ◽  
Jiang Lihua
2013 ◽  
Vol 33 (9) ◽  
pp. 2493-2496
Author(s):  
Xueqiong LIU ◽  
Gang WU ◽  
Houping DENG

Algorithms ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 128 ◽  
Author(s):  
Shuhei Denzumi ◽  
Jun Kawahara ◽  
Koji Tsuda ◽  
Hiroki Arimura ◽  
Shin-ichi Minato ◽  
...  

In this article, we propose a succinct data structure of zero-suppressed binary decision diagrams (ZDDs). A ZDD represents sets of combinations efficiently and we can perform various set operations on the ZDD without explicitly extracting combinations. Thanks to these features, ZDDs have been applied to web information retrieval, information integration, and data mining. However, to support rich manipulation of sets of combinations and update ZDDs in the future, ZDDs need too much space, which means that there is still room to be compressed. The paper introduces a new succinct data structure, called DenseZDD, for further compressing a ZDD when we do not need to conduct set operations on the ZDD but want to examine whether a given set is included in the family represented by the ZDD, and count the number of elements in the family. We also propose a hybrid method, which combines DenseZDDs with ordinary ZDDs. By numerical experiments, we show that the sizes of our data structures are three times smaller than those of ordinary ZDDs, and membership operations and random sampling on DenseZDDs are about ten times and three times faster than those on ordinary ZDDs for some datasets, respectively.


2010 ◽  
Vol 48 (10) ◽  
pp. 2998-3008 ◽  
Author(s):  
W. Todd Maddox ◽  
Jennifer Pacheco ◽  
Maia Reeves ◽  
Bo Zhu ◽  
David M. Schnyer

Author(s):  
W. Todd Maddox ◽  
J. Vincent Filoteo ◽  
J. Scott Lauritzen ◽  
Emily Connally ◽  
Kelli D. Hejl

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