Cuckoo Ring: BalancingWorkload for Locality Sensitive Hash

2006 ◽  
Author(s):  
Dingyi Han ◽  
Ting Shen ◽  
Shicong Meng ◽  
Yong Yu
Keyword(s):  
Locality Sensitive Hash

MULTI-VERSION MUSIC SEARCH USING ACOUSTIC FEATURE UNION AND EXACT SOFT MAPPING

2009 ◽  
Vol 03 (02) ◽  
pp. 209-234 ◽  
Author(s):  
YI YU ◽  
KAZUKI JOE ◽  
VINCENT ORIA ◽  
FABIAN MOERCHEN ◽  
J. STEPHEN DOWNIE ◽  
...  
Keyword(s):  
Collision Probability ◽  
Acoustic Feature ◽  
Music Retrieval ◽  
Feature Sets ◽  
Soft Mapping ◽  
Audio Features ◽  
Music Audio ◽  
Locality Sensitive Hash ◽  
Principle Of Similarity ◽  
Search Quality

Research on audio-based music retrieval has primarily concentrated on refining audio features to improve search quality. However, much less work has been done on improving the time efficiency of music audio searches. Representing music audio documents in an indexable format provides a mechanism for achieving efficiency. To address this issue, in this work Exact Locality Sensitive Mapping (ELSM) is suggested to join the concatenated feature sets and soft hash values. On this basis we propose audio-based music indexing techniques, ELSM and Soft Locality Sensitive Hash (SoftLSH) using an optimized Feature Union (FU) set of extracted audio features. Two contributions are made here. First, the principle of similarity-invariance is applied in summarizing audio feature sequences and utilized in training semantic audio representations based on regression. Second, soft hash values are pre-calculated to help locate the searching range more accurately and improve collision probability among features similar to each other. Our algorithms are implemented in a demonstration system to show how to retrieve and evaluate multi-version audio documents. Experimental evaluation over a real "multi-version" audio dataset confirms the practicality of ELSM and SoftLSH with FU and proves that our algorithms are effective for both multi-version detection (online query, one-query vs. multi-object) and same content detection (batch queries, multi-queries vs. one-object).

Irrelevance reduction with locality-sensitive hash learning for efficient cross-media retrieval

2018 ◽  
Vol 77 (22) ◽  
pp. 29435-29455
Author(s):  
Yuhua Jia ◽  
Liang Bai ◽  
Peng Wang ◽  
Jinlin Guo ◽  
Yuxiang Xie ◽  
...  
Keyword(s):  
Cross Media ◽  
Locality Sensitive Hash
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