Set Representation of Itemset for Candidate Generation with Binary Search Technique

2020 ◽  
pp. 509-520
Author(s):  
Carynthia Kharkongor ◽  
Bhabesh Nath
Keyword(s):  
Binary Search ◽  
Search Technique

Reverse maximum flow problem under the weighted Chebyshev distance

2018 ◽  
Vol 52 (4-5) ◽  
pp. 1107-1121 ◽  
Author(s):  
Javad Tayyebi ◽  
Abumoslem Mohammadi ◽  
Seyyed Mohammad Reza Kazemi
Keyword(s):  
Flow Problem ◽  
Maximum Flow ◽  
Binary Search ◽  
Second Phase ◽  
Sink Node ◽  
Search Technique ◽  
Bound Constraints ◽  
Maximum Flow Problem ◽  
Optimal Value ◽  
Two Phases

Given a network G(V, A, u) with two specific nodes, a source node s and a sink node t, the reverse maximum flow problem is to increase the capacity of some arcs (i, j) as little as possible under bound constraints on the modifications so that the maximum flow value from s to t in the modified network is lower bounded by a prescribed value v0. In this paper, we study the reverse maximum flow problem when the capacity modifications are measured by the weighted Chebyshev distance. We present an efficient algorithm to solve the problem in two phases. The first phase applies the binary search technique to find an interval containing the optimal value. The second phase uses the discrete type Newton method to obtain exactly the optimal value. Finally, some computational experiments are conducted to observe the performance of the proposed algorithm.

Randomized binary search technique

1969 ◽  
Vol 12 (2) ◽  
pp. 77-80 ◽  
Author(s):  
S. R. Arora ◽  
W. T. Dent
Keyword(s):  
Binary Search ◽  
Search Technique

COMPUTING CONSTRAINED SHORTEST SEGMENTS: BUTTERFLY WINGSPANS IN LOGARITHMIC TIME

1999 ◽  
Vol 09 (01) ◽  
pp. 53-62
Author(s):  
DAVID KIRKPATRICK ◽  
JACK SNOEYINK
Keyword(s):  
Time Algorithm ◽  
Binary Search ◽  
Binary Search Trees ◽  
Search Trees ◽  
Search Technique

We give a logarithmic-time algorithm to compute the shortest segment joining two convex n-gons A and B while avoiding another convex n-gon C. Our algorithm uses a tentative prune-and-search technique on standard representations of the polygons as arrays or balanced binary search trees.

scholarly journals The Genetic Algorithm and Binary Search Technique in the Program Path Coverage for Improving Software Testing Using Big Data

2020 ◽  
Vol 26 (4) ◽  
pp. 725-733
Author(s):  
Aysh Alhroob ◽  
Wael Alzyadat ◽  
Ayad Tareq Imam ◽  
Ghaith M. Jaradat
Keyword(s):  
Genetic Algorithm ◽  
Big Data ◽  
Software Testing ◽  
Binary Search ◽  
Search Technique ◽  
Path Coverage

DNA MOTIF IDENTIFICATION USING LPBS

2016 ◽  
Vol 78 (6-5) ◽  
Author(s):  
Hazaruddin Harun ◽  
Sharifah Lailee Syed Abdullah ◽  
Hamirul Aini Hambali
Keyword(s):  
Dna Sequences ◽  
Deoxyribonucleic Acid ◽  
Binary Search ◽  
Online Database ◽  
Search Technique ◽  
Swarm Optimization ◽  
Dna Motif ◽  
Motif Identification ◽  
Species Specific ◽  
Specific Species

In recent years, several deoxyribonucleic acid (DNA)-based approaches have been developed for species identification including DNA sequencing.  The search for motif or patterns in DNA sequences is important in many fields especially in biology. In this paper, a new particle swarm optimization (PSO) approach for discovering species-specific motifs was proposed.  The new method named as Linear-PSO with Binary Search (LPBS) is developed to discover motifs of specific species through DNA sequences.  This enhanced method integrates Linear-PSO and binary search technique to minimize the execution time and to increase the correctness in identifying the motif.  In this study, two fragments samples of ‘mitochondrial cytochrome C oxidase subunit I’ (COI or COX1) were collected from the Genbank online database. DNA sequences for the first sample are fragments of COI for one species and the second samples are a complete COI from a different species. The genome of COI was used as a reference set and other DNA sequences were used as a comparison set. The results show that the LPBS algorithm is able to discover motifs of a species when using DNA sequences from the same fragment of COI. 

An Approach to Trie Based Keyword Search for Search Engines

2017 ◽  
Vol 6 (1) ◽  
pp. 1-16
Author(s):  
Pranav Murali
Keyword(s):  
Data Structure ◽  
Search Engines ◽  
Keyword Search ◽  
Relevant Information ◽  
Binary Search ◽  
Access Time ◽  
Search Query ◽  
Search Technique ◽  
Indexing Methods ◽  
Good Improvement

Search Engines use indexing techniques to minimize the time taken to find the relevant information to a search query. They maintain a keywords list that may reside either in the memory or in the external storage, like a hard disk. While a pure binary search can be used for this purpose, it suffers from performance issue when keywords are stored in the external storage. Some implementations of search engines use a B-tree and sparse indexes to reduce access time. This paper aims at reducing the keyword access time further. It presents a keyword search technique that utilizes a combination of trie data structure and a new keyword prefixing method. Experimental results show good improvement in performance over pure binary search. The merits of incorporating trie based approach into contemporary indexing methods is also discussed. Keyword prefixing method is described and some salient steps in the process of keyword generation are outlined.

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