6 citations · 12 across the 3 of their papers we have counts for
4 papers
Extreme-SAX: Extreme Points Based Symbolic Representation for Time Series Classification
Muhammad Marwan Muhammad Fuad
Time series classification is an important problem in data mining with several applications in different domains. Because time series data are usually high dimensional, dimensional…
Modifying the Symbolic Aggregate Approximation Method to Capture Segment Trend Information
Muhammad Marwan Muhammad Fuad
The Symbolic Aggregate approXimation (SAX) is a very popular symbolic dimensionality reduction technique of time series data, as it has several advantages over other dimensionality…
Applying Nature-Inspired Optimization Algorithms for Selecting Important Timestamps to Reduce Time Series Dimensionality
Muhammad Marwan Muhammad Fuad
Time series data account for a major part of data supply available today. Time series mining handles several tasks such as classification, clustering, query-by-content, prediction,…
Towards a faster symbolic aggregate approximation method
Muhammad Marwan Muhammad Fuad, Pierre-François Marteau
The similarity search problem is one of the main problems in time series data mining. Traditionally, this problem was tackled by sequentially comparing the given query against all…