Learning to hash for indexing big data - A survey

Proceedings of the IEEE

Volumn 104, Issue 1, 2016, Pages 34-57

  Wang, Jun ^a   Liu, Wei ^b   Kumar, Sanjiv ^c   Chang, Shih Fu ^d  

^a EAST CHINA NORMAL UNIVERSITY   (China)

^b IBM T J WATSON RESEARCH CENTER   (United States)

^c GOOGLE INC   (United States)

^d Columbia University ^*  (United States)

Author keywords

Artificial neural networks; Big data; Binary codes; Indexing; Semantics; Tagging; Twitter

Indexed keywords

BIG DATA; BINARY CODES; CODES (SYMBOLS); DEEP LEARNING; HASH FUNCTIONS; INDEXING (OF INFORMATION); NEURAL NETWORKS; PATTERN MATCHING; SEMANTICS; SURVEYS;

APPROXIMATE NEAREST NEIGHBORS (ANN); CRITICAL APPLICATIONS; FUNDAMENTAL RESEARCH; LOCALITY SENSITIVE HASHING; MEMORY REQUIREMENTS; RANDOM PROJECTIONS; TAGGING; TWITTER;

NEAREST NEIGHBOR SEARCH;

EID: 84962259785     PISSN: 00189219     EISSN: 15582256     Source Type: Journal    
DOI: 10.1109/JPROC.2015.2487976     Document Type: Review

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