TextBenDS: a Generic Textual Data Benchmark for Distributed Systems

Extracting top- k keywords and documents using weighting schemes are popular techniques employed in text mining and machine learning for different analysis and retrieval tasks. The weights are usually computed in the data preprocessing step, as they are costly to update and keep track of all the mod...

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Vydané v:	Information systems frontiers Ročník 23; číslo 1; s. 81 - 100
Hlavní autori:	Truică, Ciprian-Octavian, Apostol, Elena-Simona, Darmont, Jérôme, Assent, Ira
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.02.2021 Springer Nature B.V Springer Verlag
Edícia:	Breakthroughs on Cross-Cutting Data Management, Data Analytics and Applied Data Science
Predmet:	Algorithms Benchmarks Big Data Business and Management Computation Computer networks Computer Science Control Data base management systems Data mining Datasets Document and Text Processing Ecosystems Errors Information systems IT in Business Keywords Machine learning Management of Computing and Information Systems Multidimensional approach Operations Research/Decision Theory Performance evaluation Queries Retrieval Scores Subsets Systems Theory Weighting Weighting schemes Distributed DBMSs Top keywords Distributed frameworks documents Benchmark Top-k documents Top-k keywords
ISSN:	1387-3326, 1572-9419
On-line prístup:	Získať plný text
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