On clusterization of "big data" streams

Berkovich, Simon; Liao, Duoduo

doi:10.1145/2345316.2345347

Cited by 14 publications

(8 citation statements)

References 3 publications

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“…In a smart city environment where everything is connected with an IoT architecture, such a large volume of data is generated that it has become one of the major challenges for Big Data, and there are several studies that show that the volume of data generated in recent years exceeds a zettabyte [207,208,209,210]. …”

Section: Methodsmentioning

confidence: 99%

State of the Art, Trends and Future of Bluetooth Low Energy, Near Field Communication and Visible Light Communication in the Development of Smart Cities

García

Ruiz

Gómez‐Nieto

2016

Sensors

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The current social impact of new technologies has produced major changes in all areas of society, creating the concept of a smart city supported by an electronic infrastructure, telecommunications and information technology. This paper presents a review of Bluetooth Low Energy (BLE), Near Field Communication (NFC) and Visible Light Communication (VLC) and their use and influence within different areas of the development of the smart city. The document also presents a review of Big Data Solutions for the management of information and the extraction of knowledge in an environment where things are connected by an “Internet of Things” (IoT) network. Lastly, we present how these technologies can be combined together to benefit the development of the smart city.

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Section: Methodsmentioning

confidence: 99%

State of the Art, Trends and Future of Bluetooth Low Energy, Near Field Communication and Visible Light Communication in the Development of Smart Cities

García

Ruiz

Gómez‐Nieto

2016

Sensors

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“…43 [2] 108 [3] 199 [4] 1920 [5] 3840 [6] 176236 [7] 176327 [8] 178048 [9] 179968 [10] 442567 [11] 444288 [12] 446208 [13] 819072 [14] 816896 [15] 7868160 1000  [0] 5244416 [1] 202860 [2] 202947 [3] 203166 [4] 204288 [5] 202496 [6] 442563 [7] 442782 [8] 443904 [9] 446208 [10] 799134 [11] 800256 [12] 802560 [13] 1697280 [14] 1699584 [15] 6295296 1000  00000000000001111101000 480  00000000000000111100000 Figure 5 : Sample result of FuzzyFind Dictionary and shows that two indices with hamming distance of less or equal than two has at least one same mapping index.…”

Section: For Testing Fuzzyfind Dictionary We Needs To Test All Cases mentioning

confidence: 99%

“…The interaction between a search engine and database requires that the database structure to be consistent with a search engine to search quickly, easily, and efficiently. Golay Coding clustering technique which has faster time complexity in comparison with previous conventional methods such as K-means, spectral clustering and hierarchical clustering [8,11] . Also the traditional method 1 National Aeronautics and Space Administration (NASA) of clustering cannot cover fuzzy logic.…”

Section: Introductionmentioning

confidence: 99%

Construction of FuzzyFind Dictionary using Golay Coding Transformation for Searching Applications

Kowsari¹,

Yammahi²,

Bari³

et al. 2015

ijacsa

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searching through a large volume of data is very critical for companies, scientists, and searching engines applications due to time complexity and memory complexity. In this paper, a new technique of generating FuzzyFind Dictionary for text mining was introduced. We simply mapped the 23 bits of the English alphabet into a FuzzyFind Dictionary or more than 23 bits by using more FuzzyFind Dictionary, and reflecting the presence or absence of particular letters. This representation preserves closeness of word distortions in terms of closeness of the created binary vectors within Hamming distance of 2 deviations. This paper talks about the Golay Coding Transformation Hash Table and how it can be used on a FuzzyFind Dictionary as a new technology for using in searching through big data. This method is introduced by linear time complexity for generating the dictionary and constant time complexity to access the data and update by new data sets, also updating for new data sets is linear time depends on new data points. This technique is based on searching only for letters of English that each segment has 23 bits, and also we have more than 23-bit and also it could work with more segments as reference table.

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“…Also called meaning of data, this hidden information can be localized through a simple observation of the desired clustering (posteriori), without prior knowledge of the applied clustering criteria. The computational Big data processing and clustering technique suggested here as a 23-bit template will allow the information retrieval of this valuable and insightful information [13].…”

Section: -Bit Metaknowledge Vector Template For Big Data Insigmentioning

confidence: 99%

“…When other research fails, the Golay Coding approach becomes very useful. The challenge that arises from an extension of the conventional searching methodology hinges upon developing constructive attributes that are in turn used to develop the Metaknowledge of 23-bit vector templates [13].…”

Section: -Bit Metaknowledge Vector Template For Big Data Insigmentioning

confidence: 99%

23-bit metaknowledge template towards Big Data knowledge discovery and management

Bari

Vichr²,

Kowsari

et al. 2014

2014 International Conference on Data Science and Advanced Analytics (DSAA)

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the global influence of Big Data is not only growing but seemingly endless. The trend is leaning towards knowledge that is attained easily and quickly from massive pools of Big Data. Today we are living in the technological world that Dr. Usama Fayyad and his distinguished research fellows discussed in the introductory explanations of Knowledge Discovery in Databases (KDD) [1] predicted nearly two decades ago. Indeed, they were precise in their outlook on Big Data analytics. In fact, the continued improvement of the interoperability of machine learning, statistics, database building and querying fused to create this increasingly popular science-Data Mining and Knowledge Discovery. The next generation computational theories are geared towards helping to extract insightful knowledge from even larger volumes of data at higher rates of speed. As the trend increases in popularity, the need for a highly adaptive solution for knowledge discovery will be necessary. In this research paper, we are introducing the investigation and development of 23 bit-questions for a Metaknowledge template for Big Data Processing and clustering purposes. This research aims to demonstrate the construction of this methodology and proves the validity and the beneficial utilization that brings Knowledge Discovery from Big Data.

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On clusterization of "big data" streams

Cited by 14 publications

References 3 publications

State of the Art, Trends and Future of Bluetooth Low Energy, Near Field Communication and Visible Light Communication in the Development of Smart Cities

State of the Art, Trends and Future of Bluetooth Low Energy, Near Field Communication and Visible Light Communication in the Development of Smart Cities

Construction of FuzzyFind Dictionary using Golay Coding Transformation for Searching Applications

23-bit metaknowledge template towards Big Data knowledge discovery and management

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