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Title: Automatic identification of abstract online groups

Abstract

Online abstract groups, in which members aren't explicitly connected, can be automatically identified by computer-implemented methods. The methods involve harvesting records from social media and extracting content-based and structure-based features from each record. Each record includes a social-media posting and is associated with one or more entities. Each feature is stored on a data storage device and includes a computer-readable representation of an attribute of one or more records. The methods further involve grouping records into record groups according to the features of each record. Further still the methods involve calculating an n-dimensional surface representing each record group and defining an outlier as a record having feature-based distances measured from every n-dimensional surface that exceed a threshold value. Each of the n-dimensional surfaces is described by a footprint that characterizes the respective record group as an online abstract group.

Inventors:
; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1129185
Patent Number(s):
8,700,629
Application Number:
13/540,759
Assignee:
Battelle Memorial Institute (Richland, WA) PNNL
DOE Contract Number:  
AC05-76RLO1830
Resource Type:
Patent
Resource Relation:
Patent File Date: 2012 Jul 03
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Engel, David W, Gregory, Michelle L, Bell, Eric B, Cowell, Andrew J, and Piatt, Andrew W. Automatic identification of abstract online groups. United States: N. p., 2014. Web.
Engel, David W, Gregory, Michelle L, Bell, Eric B, Cowell, Andrew J, & Piatt, Andrew W. Automatic identification of abstract online groups. United States.
Engel, David W, Gregory, Michelle L, Bell, Eric B, Cowell, Andrew J, and Piatt, Andrew W. Tue . "Automatic identification of abstract online groups". United States. https://www.osti.gov/servlets/purl/1129185.
@article{osti_1129185,
title = {Automatic identification of abstract online groups},
author = {Engel, David W and Gregory, Michelle L and Bell, Eric B and Cowell, Andrew J and Piatt, Andrew W},
abstractNote = {Online abstract groups, in which members aren't explicitly connected, can be automatically identified by computer-implemented methods. The methods involve harvesting records from social media and extracting content-based and structure-based features from each record. Each record includes a social-media posting and is associated with one or more entities. Each feature is stored on a data storage device and includes a computer-readable representation of an attribute of one or more records. The methods further involve grouping records into record groups according to the features of each record. Further still the methods involve calculating an n-dimensional surface representing each record group and defining an outlier as a record having feature-based distances measured from every n-dimensional surface that exceed a threshold value. Each of the n-dimensional surfaces is described by a footprint that characterizes the respective record group as an online abstract group.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Apr 15 00:00:00 EDT 2014},
month = {Tue Apr 15 00:00:00 EDT 2014}
}

Patent:

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