FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2553500715> ?p ?o ?g. }

• W2553500715 endingPage "30" @default.
• W2553500715 startingPage "15" @default.
• W2553500715 abstract "In the era of big data, we are facing with an immense volume and high velocity of data with complex structures. Data can be produced by online and offline transactions, social networks, sensors and through our daily life activities. A proper processing of big data can result in informative, intelligent and relevant decision making completed in various areas, such as medical and healthcare, business, management and government. To handle big data more efficiently, new research paradigm has been engaged but the ways of thinking about big data call for further long-term innovative pursuits. Fuzzy sets have been employed for big data processing due to their abilities to represent and quantify aspects of uncertainty. Several innovative approaches within the framework of Granular Computing have been proposed. To summarize the current contributions and present an outlook of further developments, this overview addresses three aspects: (1) We review the recent studies from two distinct views. The first point of view focuses on what types of fuzzy set techniques have been adopted. It identifies clear trends as to the usage of fuzzy sets in big data processing. Another viewpoint focuses on the explanation of the benefits of fuzzy sets in big data problems. We analyze when and why fuzzy sets work in these problems. (2) We present a critical review of the existing problems and discuss the current challenges of big data, which could be potentially and partially solved in the framework of fuzzy sets. (3) Based on some principles, we infer the possible trends of using fuzzy sets in big data processing. We stress that some more sophisticated augmentations of fuzzy sets and their integrations with other tools could offer a novel promising processing environment." @default.
• W2553500715 created "2016-11-30" @default.
• W2553500715 creator A5003799782 @default.
• W2553500715 creator A5041873075 @default.
• W2553500715 creator A5073568638 @default.
• W2553500715 date "2017-02-01" @default.
• W2553500715 modified "2023-10-03" @default.
• W2553500715 title "An overview on the roles of fuzzy set techniques in big data processing: Trends, challenges and opportunities" @default.
• W2553500715 cites W1042911521 @default.
• W2553500715 cites W1152304712 @default.
• W2553500715 cites W1176839007 @default.
• W2553500715 cites W1255007073 @default.
• W2553500715 cites W1529756603 @default.
• W2553500715 cites W1673779392 @default.
• W2553500715 cites W1811592017 @default.
• W2553500715 cites W1838153851 @default.
• W2553500715 cites W1923399994 @default.
• W2553500715 cites W1965563268 @default.
• W2553500715 cites W1966241942 @default.
• W2553500715 cites W1968375151 @default.
• W2553500715 cites W1969267249 @default.
• W2553500715 cites W1970718874 @default.
• W2553500715 cites W1978062397 @default.
• W2553500715 cites W1990766815 @default.
• W2553500715 cites W1991308169 @default.
• W2553500715 cites W1997687853 @default.
• W2553500715 cites W1997803906 @default.
• W2553500715 cites W2001590979 @default.
• W2553500715 cites W2014859876 @default.
• W2553500715 cites W2017374559 @default.
• W2553500715 cites W2023594955 @default.
• W2553500715 cites W2027654459 @default.
• W2553500715 cites W2032395696 @default.
• W2553500715 cites W2033174805 @default.
• W2553500715 cites W2036715518 @default.
• W2553500715 cites W2054844101 @default.
• W2553500715 cites W2058063871 @default.
• W2553500715 cites W2058392922 @default.
• W2553500715 cites W2060137371 @default.
• W2553500715 cites W2068181924 @default.
• W2553500715 cites W2076684951 @default.
• W2553500715 cites W2077190206 @default.
• W2553500715 cites W2078206416 @default.
• W2553500715 cites W2080453063 @default.
• W2553500715 cites W2081829983 @default.
• W2553500715 cites W2085342512 @default.
• W2553500715 cites W2093358008 @default.
• W2553500715 cites W2097403045 @default.
• W2553500715 cites W2098149468 @default.
• W2553500715 cites W2105683156 @default.
• W2553500715 cites W2108473620 @default.
• W2553500715 cites W2109574129 @default.
• W2553500715 cites W2112257737 @default.
• W2553500715 cites W2113709784 @default.
• W2553500715 cites W2117827905 @default.
• W2553500715 cites W2118417438 @default.
• W2553500715 cites W2124450561 @default.
• W2553500715 cites W2124491466 @default.
• W2553500715 cites W2128964655 @default.
• W2553500715 cites W2133757074 @default.
• W2553500715 cites W2135074661 @default.
• W2553500715 cites W2148002238 @default.
• W2553500715 cites W2154148713 @default.
• W2553500715 cites W2159588611 @default.
• W2553500715 cites W2171895522 @default.
• W2553500715 cites W2173073476 @default.
• W2553500715 cites W2173315138 @default.
• W2553500715 cites W2178421650 @default.
• W2553500715 cites W2178918608 @default.
• W2553500715 cites W2184448088 @default.
• W2553500715 cites W2186648744 @default.
• W2553500715 cites W2190850610 @default.
• W2553500715 cites W2192540070 @default.
• W2553500715 cites W2215376118 @default.
• W2553500715 cites W2220188468 @default.
• W2553500715 cites W2247181270 @default.
• W2553500715 cites W2276298621 @default.
• W2553500715 cites W2281814488 @default.
• W2553500715 cites W2291962372 @default.
• W2553500715 cites W2294329743 @default.
• W2553500715 cites W2310218092 @default.
• W2553500715 cites W2331687785 @default.
• W2553500715 cites W2332302367 @default.
• W2553500715 cites W2409575000 @default.
• W2553500715 cites W2474884296 @default.
• W2553500715 cites W2511003225 @default.
• W2553500715 cites W2972752804 @default.
• W2553500715 cites W4211007335 @default.
• W2553500715 cites W4236154462 @default.
• W2553500715 cites W4248160574 @default.
• W2553500715 cites W432457081 @default.
• W2553500715 cites W585037961 @default.
• W2553500715 cites W794265031 @default.
• W2553500715 cites W841229804 @default.
• W2553500715 doi "https://doi.org/10.1016/j.knosys.2016.11.008" @default.
• W2553500715 hasPublicationYear "2017" @default.
• W2553500715 type Work @default.
• W2553500715 sameAs 2553500715 @default.

• next