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The social media stream clustering algorithm from [85]

Stream-dashboard : a big data stream clustering framework with applications to social media streams.

Stream-dashboard : a big data stream clustering framework with applications to social media streams.

... the clustering model output of a clustering ...the clustering ten- dency of the data ...any clustering algorithm will find some clusters in any set of ...detect clustering ...

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TweeProfiles4: a weighted multidimensional stream clustering algorithm

TweeProfiles4: a weighted multidimensional stream clustering algorithm

... lows clustering Twitter data streams on real-time, taking into account multiple ...the clustering algorithm, this dimension is being implicitly considered, so by this perspective it was decided to ...

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LeaDen Stream: A Leader Density Based Clustering Algorithm over Evolving Data Stream

LeaDen Stream: A Leader Density Based Clustering Algorithm over Evolving Data Stream

... density-based clustering al- gorithm using leader clustering. The algorithm is based on a two-phase ...the clustering while maintaining the cluster ...data from noise by introducing ...

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Clustering media items stemming from multiple social networks

Clustering media items stemming from multiple social networks

... 5.2. Video-contained-in-Video Workflow To detect whether a given video A is a subsegment of another video B, we propose a similar approach as outlined in the previous subsection, with the sole difference that we need to ...

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A Clustering Algorithm in Complex Social Networks

A Clustering Algorithm in Complex Social Networks

... 1. INTRODUCTION Complex networks are not formally defined but are characterized by dynamically changing big networks which are backbones of complex systems. The origin of complex networks can be looked back with the ...

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An Efficient Clustering Process using Optimized C Means Algorithm in Social Media Data

An Efficient Clustering Process using Optimized C Means Algorithm in Social Media Data

... robust clustering algorithms play an important role in extracting useful information in large ...other. Clustering can be used to quantize the available data, to extract a set of cluster prototypes for the ...

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IMPLEMENTATION OF ALGORITHM OUTPUT GRANULARITY APPROACH IN CLUSTERING ALGORITHM FOR MOBILE DATA STREAM MINING

IMPLEMENTATION OF ALGORITHM OUTPUT GRANULARITY APPROACH IN CLUSTERING ALGORITHM FOR MOBILE DATA STREAM MINING

... data from other sensors such as bio/body sensors. Data from mobile users/devices is becoming increasingly important for numerous applications, including urban modeling, transportation, and more recently for ...

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A visual framework for clustering memes in social media

A visual framework for clustering memes in social media

... online social network data, understanding and analyzing them are becoming more chal- ...of clustering memes shares some similarity with clustering texts, but they are also intrinsically ...example, ...

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Hybrid Clustering Algorithm for Time Series Data Stream: Current State of the Art

Hybrid Clustering Algorithm for Time Series Data Stream: Current State of the Art

... based clustering of time series data ...for clustering of time series based on their constructional ...out from the time series data sets. The feature measures are extracted from each single ...

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Social Network Analysis Based on BSP Clustering Algorithm

Social Network Analysis Based on BSP Clustering Algorithm

... network clustering analysis, which is different from traditional clustering problem, divides objects into classes based on their links as well as their ...of social network clustering ...

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A Hybrid Approach to Semantic Hashtag Clustering in Social Media

A Hybrid Approach to Semantic Hashtag Clustering in Social Media

... sensus clustering by way of comparing different sets of clusters, such as “set matching” [4], “adjusted Rand distance” [7], “variation of information” [12], and “normalized mutual in- formation” ...The ...

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Deductive and Inductive Stream Reasoning for Semantic Social Media Analytics

Deductive and Inductive Stream Reasoning for Semantic Social Media Analytics

... definedastheusersofGluesocialnetwork.Fortrainingmodelswesampleasubsetfromthepopulation. Then, based on the sample, the SUNS constructs data matrices by transforming the set ...

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Deductive and Inductive Stream Reasoning for Semantic Social Media Analytics

Deductive and Inductive Stream Reasoning for Semantic Social Media Analytics

... Existing techniques for perform- ing this reasoning task include incre- mental maintenance of materialized views in logic, 15 graph databases, 16 extensions of the RETE algorithm for incremental rule-based reason- ...

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Automatic Summarization Of Tweet From Social Media Using Tweet Classification and Clustering(Based On GPU)

Automatic Summarization Of Tweet From Social Media Using Tweet Classification and Clustering(Based On GPU)

... -Social media is increased in presence and importance in society. A social network service consists of a representation of each ...user. Social networking sites allow users to communicate with ...

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Real Time analysis of social media text using stream computing

Real Time analysis of social media text using stream computing

... teams, social engagement and community staff, agencies and sales ...of social media channels from blogging to internet video to internet ...through social media ...

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Parallel Clustering of High Dimensional Social Media Data Streams

Parallel Clustering of High Dimensional Social Media Data Streams

... SYNCINIT, clustering bolt sends SYNCREQ to tell sync coordinator that it’s ready to receive synchronization ...SYNCREQ from clustering bolts, sync coordinator constructs CDELTAS message, which ...

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Parallel Clustering of High Dimensional Social Media Data Streams

Parallel Clustering of High Dimensional Social Media Data Streams

... application: social media data stream ...and social network ...real-time social media stream clustering through parallelization in Cloud ...most stream ...

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Event identification in social media using classification-clustering framework

Event identification in social media using classification-clustering framework

... information from microblog documents. It obtains the name list of locations from geotagged tweets and adds positional information to tweets by matching the location ...(CDE) from tweets. They use the ...

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Social Media Topic Categorization Using Hierarchical Clustering Approach

Social Media Topic Categorization Using Hierarchical Clustering Approach

... A. Conclusion Data mining is a concept of analyzing the data using the automated computational algorithms. In this context, these algorithms are applied on data for recovering the application desired patterns. There are ...

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