Big Data Stream Analytics & Its Applications
Speaker: Latifur Rahman Khan – Plano, TX, United StatesTopic(s): Information Systems, Search, Information Retrieval, Database Systems, Data Mining, Data Science
Abstract
Data streams are continuous flows of data. Examples of data streams include network traffic, sensor data, call center records and so on. Data streams demonstrate several unique properties that together conform to the characteristics of big data (i.e., volume, velocity, variety and veracity) and add challenges to data mining. In this talk, I will present an organized picture on how to handle various data mining/machine learning techniques in data streams. In addition, I will present a number of stream applications such as adaptive website fingerprinting, textual stream classification, new political actor identification over textual stream, and domain adaptation.
This research was funded in part by NSF, NASA, Air Force Office of Scientific Research (AFOSR), NSA, IBM Research, and Raytheon.
About this Lecture
Number of Slides: 50Duration: 60 minutes
Languages Available: English
Last Updated:
Request this Lecture
To request this particular lecture, please complete this online form.
Request a Tour
To request a tour with this speaker, please complete this online form.
All requests will be sent to ACM headquarters for review.