[PDF] Top 20 Efficient analysis of data streams
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Efficient analysis of data streams
... a data stream to be unbounded in size by which we mean that there is no time point where the data stream ...in data streams found in meteorology, the stock market, online shopping and social ... See full document
132
Regular Programming Over Data Streams
... k | A |-th smallest element of A . It is a well-known lower bound that computing medianp A q or select k pAq in one pass over the elements of A requires |A| space, and similar lower bounds on exact computation have ... See full document
165
Dynamic and on demand data streams
... the analysis of data produced by high energy physics (HEP) experiments is the efficiency of the data processing on the same data ...of data taking is typically a collection of values ... See full document
8
REAL TIME DATA SEARCH OPTIMIZATION: AN OVERVIEW
... of data stream analysis is the unknown dataset ...of data stream should follow a special analysis to find the error ...surveillance analysis as an application in mining data ... See full document
7
Correlation clustering in data streams
... dynamic data stream ...develop data structures based on linear sketches that allow the “quality” of a given node- partition to be ...these data structures with convex programming and sampling ... See full document
11
State-of-the-art on clustering data streams
... the data dis- ...represented data points, their linear sum LS, and their squared sum ...streaming data, there might not always be enough time to reach leaf level to insert the ...fast streams, ... See full document
27
Twitter Sentiment in Data Streams with Perceptron
... The perceptron algorithm requires a learning rate on which to weight the rate of learning for each sample trained upon. The learning rate is crucial in the training, and different learning rates may product more ... See full document
6
From Sensor Data Streams to Linked Streaming Data: a survey of main approaches
... This data can be used both in simple and more complex ...if data from the user’s calendar is combined with his physical location, then appointments can be automatically changed if the system infers that all ... See full document
11
Hash Kernels for Structured Data
... Firstly, we show that the sampling schemes of Kontorovich (2007) and Rahimi and Recht (2008) can be applied to a considerably larger class of kernels than originally suggested—the authors only consider languages and ... See full document
23
Weighted Clustering and Evolutionary Analysis of Hybrid Attributes Data Streams
... 4) Analysis and conclusions of experimental results It can often get a better clustering quality than WKMeans algorithm first using two-step projected clustering method and then merging the clustering results for ... See full document
8
Modeling and Querying Data Series and Data Streams with Uncertainty
... consume data that is intrinsically uncertain and error-prone. An uncertain data series is a series whose point values are ...uncertain data stream is a data stream whose tuples are ... See full document
178
Security Enhancement and Privacy Preserving Of Big Data
... authentication, data, generic levels ...big data i.e. data preparation; effective online analysis, semantic techniques, and handling of data streams; social analytics, value ... See full document
5
WMFP-Outlier: An Efficient Maximal Frequent-Pattern-Based Outlier Detection Approach for Weighted Data Streams
... ing the sub-optimal efficiency of outlier detection via the FindFPOF method, an improved frequent- pattern-based outlier detection approach, name- ly, LFP [17], was proposed, which used the ratio of the longest length ... See full document
17
An Efficient Approach to Enhance Classifier and Cluster Ensembles Using Genetic algorithms for Mining Drifting Data Streams
... In order to improve the accuracy and error rate of traditional ensemble models, we propose a new ensemble model which combines both classifiers and clusters together and utilizes genetic[r] ... See full document
5
Large & Complex Data Streams using Big Data
... retrieve data in a significantly short amount of time. The relevancy of data lies with researcher’s ability to access such results in a timely ...and efficient. The retrieval process of spacecraft ... See full document
5
An Efficient Indexing Structure for Ensemble Classification of Data Streams Using Forest Tree Mechanism
... DATA stream classification represents one of the most important tasks in data stream mining, which has been popularly used in real-time intrusion detection, spam filtering, and malicious website ... See full document
5
Efficient object tracking in WAAS data streams
... Wide area airborne surveillance (WAAS) systems are a new class of remote sensing imagers which have many military and civilian applications. These systems are characterized by long loi- ter times (extended imaging time ... See full document
75
Annotations in data streams
... The data stream model has become a popular abstraction when designing algorithms that process network traffic and massive data sets [4, ...high-throughput data processing ...massive data sets ... See full document
23
Efficient Online Summarization of Microblogging Streams
... of data generated on microblogging services are making sum- marization ...filtered streams. Input data has to be saved and analyzed several times, in or- der to detect underlying events and then ... See full document
5
Filtering social media data streams
... In the paper “information overload: a temporal approach” (Schick, et al., 1990) the problem of information overload is discussed. The paper provides a more precise definition of information overload than previously ... See full document
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