Pattern recognition and event detection on IoT data-streams
Big data streams are possibly one of the most essential underlying notions. However, data
streams are often challenging to handle owing to their rapid pace and limited information …
streams are often challenging to handle owing to their rapid pace and limited information …
Large scale implementations for twitter sentiment classification
Sentiment Analysis on Twitter Data is indeed a challenging problem due to the nature,
diversity and volume of the data. People tend to express their feelings freely, which makes …
diversity and volume of the data. People tend to express their feelings freely, which makes …
[PDF][PDF] Large Scale Sentiment Analysis on Twitter with Spark.
Sentiment analysis on Twitter data has attracted much attention recently. One of the system's
key features, is the immediacy in communication with other users in an easy, user-friendly …
key features, is the immediacy in communication with other users in an easy, user-friendly …
WiCHORD+: A Scalable, Sustainable, and P2P Chord-Based Ecosystem for Smart Agriculture Applications
In the evolving landscape of Industry 4.0, the convergence of peer-to-peer (P2P) systems,
LoRa-enabled wireless sensor networks (WSNs), and distributed hash tables (DHTs) …
LoRa-enabled wireless sensor networks (WSNs), and distributed hash tables (DHTs) …
Improving distance-join query processing with voronoi-diagram based partitioning in spatialhadoop
SpatialHadoop is an extended MapReduce framework supporting global indexing
techniques that partition spatial datasets across several machines and improve spatial query …
techniques that partition spatial datasets across several machines and improve spatial query …
Efficient distance join query processing in distributed spatial data management systems
Due to the ubiquitous use of spatial data applications and the large amounts of such data
these applications use, the processing of large-scale distance joins in distributed systems is …
these applications use, the processing of large-scale distance joins in distributed systems is …
Efficient distributed algorithms for distance join queries in spark-based spatial analytics systems
ABSTRACT Apache Sedona (formerly GeoSpark) is a new in-memory cluster computing
system for processing large-scale spatial data, which extends the core of Apache Spark to …
system for processing large-scale spatial data, which extends the core of Apache Spark to …
Efficient processing of all-k-nearest-neighbor queries in the MapReduce programming framework
Numerous modern applications, from social networking to astronomy, need efficient
answering of queries on spatial data. One such query is the All k Nearest-Neighbor Query …
answering of queries on spatial data. One such query is the All k Nearest-Neighbor Query …
Efficient large-scale distance-based join queries in spatialhadoop
Abstract Efficient processing of Distance-Based Join Queries (DBJQs) in spatial databases
is of paramount importance in many application domains. The most representative and …
is of paramount importance in many application domains. The most representative and …
[PDF][PDF] Method to implement K-NN machine learningto classify data privacy in IoT environment
Internet of Things technology allows many devices to connect with each other. The
interaction could be between humans and devices or between devices itself. In fact, the data …
interaction could be between humans and devices or between devices itself. In fact, the data …