scholarly journals Dynamic search-space pruning techniques in path sensitization

1994 ◽  
Author(s):  
João P. Marques Silva ◽  
Karem A. Sakallah
Keyword(s):  
Search Space ◽  
Path Sensitization ◽  
Dynamic Search ◽  
Search Space Pruning ◽  
Pruning Techniques

scholarly journals Meta-Interpretive Learning Using HEX-Programs

2019 ◽  
Author(s):  
Tobias Kaminski ◽  
Thomas Eiter ◽  
Katsumi Inoue
Keyword(s):  
Logic Programming ◽  
Inductive Logic Programming ◽  
Inductive Logic ◽  
Answer Set Programming ◽  
Search Space ◽  
Recent Approach ◽  
Performance Gains ◽  
Pruning Techniques ◽  
Answer Set

Meta-Interpretive Learning (MIL) is a recent approach for Inductive Logic Programming (ILP) implemented in Prolog. Alternatively, MIL-problems can be solved by using Answer Set Programming (ASP), which may result in performance gains due to efficient conflict propagation. However, a straightforward MIL-encoding results in a huge size of the ground program and search space. To address these challenges, we encode MIL in the HEX-extension of ASP, which mitigates grounding issues, and we develop novel pruning techniques.

New Policy of Maximal Frequent Itemsets in Data Stream Mining

2010 ◽  
Vol 26-28 ◽  
pp. 118-122
Author(s):  
Chong Huan Xu ◽  
Chun Hua Ju
Keyword(s):  
Stream Flow ◽  
Data Stream ◽  
Search Space ◽  
Frequent Itemsets ◽  
Stream Flows ◽  
Algorithm Construct ◽  
Maximal Frequent Itemsets ◽  
Core Idea ◽  
Basic Window ◽  
Pruning Techniques

According to the features of data streams and combined sliding window, a new algorithm A-MFI which is based on self-adjusting and orderly-compound policy for mining maximal frequent itemsets in data stream is proposed. This algorithm which is based on basic window updates information from data stream flow fragments and scans the stream only once to gain and store it in frequent itemsets list when the data stream flows. The core idea of this algorithm: construct self-adjusting and orderly-compound FP-tree, use mixed subset pruning techniques to reduce the search space, merge nodes which has equal minsup in the same branch and compress to generate the orderly-compound FP-tree to avoid superset checking when mining maximal frequent itemsets. The experimental results show that the algorithm has higher efficiency in time and space, and also has good scalability.

Effective Search-Space Pruning for Solvers of String Equations, Regular Expressions and Length Constraints

2015 ◽  
pp. 235-254 ◽  
Author(s):  
Yunhui Zheng ◽  
Vijay Ganesh ◽  
Sanu Subramanian ◽  
Omer Tripp ◽  
Julian Dolby ◽  
...  
Keyword(s):  
Search Space ◽  
Regular Expressions ◽  
Search Space Pruning

A method of search space pruning based on search state dominance

1994 ◽  
Vol 25 (4) ◽  
pp. 1-12
Author(s):  
Takayuki Fujino ◽  
Hideo Fujiwara
Keyword(s):  
Search Space ◽  
Search Space Pruning
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