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Title: Exploiting Social Media Sensor Networks through Novel Data Fusion Techniques

Abstract

Unprecedented amounts of data are continuously being generated by sensors (“hard” data) and by humans (“soft” data), and this data needs to be exploited to its full potential. The first step in exploiting this data is determine how the hard and soft data are related to each other. In this project we fuse hard and soft data, using the attributes of each (e.g., time and space), to gain more information about interesting events. Next, we attempt to use social networking textual data to predict the present (i.e., predict that an interesting event is occurring and details about the event) using data mining, machine learning, natural language processing, and text analysis techniques.

Authors:
 [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1431510
Report Number(s):
SAND2017-12939
659150
DOE Contract Number:  
NA0003525
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Kouri, Tina. Exploiting Social Media Sensor Networks through Novel Data Fusion Techniques. United States: N. p., 2017. Web. doi:10.2172/1431510.
Kouri, Tina. Exploiting Social Media Sensor Networks through Novel Data Fusion Techniques. United States. doi:10.2172/1431510.
Kouri, Tina. Wed . "Exploiting Social Media Sensor Networks through Novel Data Fusion Techniques". United States. doi:10.2172/1431510. https://www.osti.gov/servlets/purl/1431510.
@article{osti_1431510,
title = {Exploiting Social Media Sensor Networks through Novel Data Fusion Techniques},
author = {Kouri, Tina},
abstractNote = {Unprecedented amounts of data are continuously being generated by sensors (“hard” data) and by humans (“soft” data), and this data needs to be exploited to its full potential. The first step in exploiting this data is determine how the hard and soft data are related to each other. In this project we fuse hard and soft data, using the attributes of each (e.g., time and space), to gain more information about interesting events. Next, we attempt to use social networking textual data to predict the present (i.e., predict that an interesting event is occurring and details about the event) using data mining, machine learning, natural language processing, and text analysis techniques.},
doi = {10.2172/1431510},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2017},
month = {11}
}

Technical Report:

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