Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 임혜숙 | * |
dc.date.accessioned | 2022-08-02T16:30:39Z | - |
dc.date.available | 2022-08-02T16:30:39Z | - |
dc.date.issued | 2021 | * |
dc.identifier.issn | 0018-9340 | * |
dc.identifier.issn | 1557-9956 | * |
dc.identifier.other | OAK-31833 | * |
dc.identifier.uri | https://dspace.ewha.ac.kr/handle/2015.oak/261639 | - |
dc.description.abstract | As a challenging attempt to replace a traditional data structure with a learned model, this paper proposes a learned functional Bloom filter (L-FBF) for a key-value storage. The learned model in the proposed L-FBF learns the characteristics and the distribution of given data and classifies each input. It is shown through theoretical analysis that the L-FBF provides a lower search failure rate than a single FBF in the same memory size, while providing the same semantic guarantees. For model training, character-level neural networks are used with pretrained embeddings. In experiments, four types of different character-level neural networks are trained: a single gated recurrent unit (GRU), two GRUs, a single long short-term memory (LSTM), and a single one-dimensional convolutional neural network (1D-CNN). Experimental results prove the validity of theoretical results, and show that the L-FBF reduces the search failures by 82.8% to 83.9% when compared with a single FBF under the same amount of memory used. | * |
dc.language | English | * |
dc.publisher | IEEE COMPUTER SOC | * |
dc.subject | Data structures | * |
dc.subject | Data models | * |
dc.subject | Programming | * |
dc.subject | Memory management | * |
dc.subject | Indexes | * |
dc.subject | Task analysis | * |
dc.subject | Neural networks | * |
dc.subject | Key-value storage | * |
dc.subject | functional Bloom filter | * |
dc.subject | deep learning | * |
dc.subject | search failure | * |
dc.title | Learned FBF: Learning-Based Functional Bloom Filter for Key-Value Storage | * |
dc.type | Article | * |
dc.relation.issue | 8 | * |
dc.relation.volume | 71 | * |
dc.relation.index | SCIE | * |
dc.relation.index | SCOPUS | * |
dc.relation.startpage | 1928 | * |
dc.relation.lastpage | 1938 | * |
dc.relation.journaltitle | IEEE TRANSACTIONS ON COMPUTERS | * |
dc.identifier.doi | 10.1109/TC.2021.3112079 | * |
dc.identifier.wosid | WOS:000822371000002 | * |
dc.identifier.scopusid | 2-s2.0-85115137735 | * |
dc.author.google | Byun, Hayoung | * |
dc.author.google | Lim, Hyesook | * |
dc.contributor.scopusid | 임혜숙(7403095209) | * |
dc.date.modifydate | 20240419140241 | * |