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1
IMMERSE: Interactive Mentoring for Multimodal Experiences in Realistic Social Encounters
In: DTIC (2015)
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2
Auditory Perception in an Open Space: Detection and Recognition
In: DTIC (2015)
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3
Document Image Parsing and Understanding using Neuromorphic Architecture
In: DTIC (2015)
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4
Decision Allocation of C2 System Based on ULMADM
In: DTIC (2014)
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5
Uncertainty Can Increase Explanatory Credibility
In: DTIC (2013)
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6
Measuring Collective Intelligence in Human-Machine Systems
In: DTIC (2013)
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7
Performance Evaluation of a Semantic Perception Classifier
In: DTIC (2013)
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8
Military Operating Room of the Future
In: DTIC (2012)
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9
Representing and Reasoning with Functional Knowledge for Spatial Language Understanding
In: DTIC (2011)
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10
The SRI NIST 2010 Speaker Recognition Evaluation System (PREPRINT)
In: DTIC (2011)
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11
Trends in Human-Computer Interaction to Support Future Intelligence Analysis Capabilities
In: DTIC (2011)
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12
A Concept Map Knowledge Model of Intelligence Analysis
In: DTIC (2011)
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13
Transfer Learning in Integrated Cognitive Systems
In: DTIC (2010)
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14
Analysis of Discourse Accent and Discursive Practices I&W
In: DTIC (2010)
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15
Transformational Impact of "Digital Natives" on Cultures, Commerce and Societies
In: DTIC (2010)
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16
Rapidly Customizable Spoken Dialogue Systems
In: DTIC (2009)
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17
Detecting Age in Online Chat
In: DTIC (2009)
Abstract: Over 90 % of teens in the United States use the Internet, and many use it for social interaction. Due to the faceless nature of digital communication, criminals can easily pose as legitimate users to build friendship and trust with potential victims. Even though fewer youths are going to chat rooms and talking to people they do not know, the number of youths receiving aggressive solicitations for offline contact has not declined. Most sexual solicitations go unreported to law enforcement and parents. Though it is a crime for an adult to sexually exploit a minor, it is not always a crime for teens to solicit other teens. It would be of great help to law enforcement agencies if they could automatically detect adults soliciting teens versus teens soliciting other teens in online chat. This study analyzes the effectiveness of different machine learning techniques to distinguish chat conversation by teens and adults. Using proposed techniques, we classified teen and adult conversations with an accuracy of 86 %. The goal of this research is to build an automatic recognition system of adults conversing with teens, capable of detecting predators and alerting agencies or parents of possible inappropriate conversations. ; The original document contains color images.
Keyword: *AGE DETECTION; *AGE DISTRIBUTION; *CHAT GROUPS; *CHAT ROOMS; *COMPUTER CRIMES; *INTERNET; *ONLINE SYSTEMS; *PATTERN RECOGNITION; *SOCIAL COMMUNICATION; ADULTS; AUTHORSHIP PROFILING; AUTOMATIC; CASUALTIES; Command; Computer Programming and Software; Control and Communications Systems; CRIMINOLOGY; CYBERTERRORISM; DIGITAL COMMUNICATIONS; FAMILY MEMBERS; Human Factors Engineering & Man Machine System; HUMAN RELATIONS; Information Science; INSTANT MESSAGING; LAW ENFORCEMENT; LEARNING; LEARNING MACHINES; Linguistics; METADATA; METHODOLOGY; N-GRAMS; NAIVE BAYES CLASSIFIERS; OFFLINE SYSTEMS; ONLINE CHAT; RECOGNITION; Sociology and Law; SOLICITATIONS; STOP WORDS; SUPPORT VECTOR MACHINES; THESES; UNITED STATES; VOICE COMMUNICATIONS
URL: http://www.dtic.mil/docs/citations/ADA508858
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA508858
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18
Effective Presentation Media for Passenger Safety I: Comprehension of Briefing Card Pictorials and Pictograms
In: DTIC (2008)
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19
A Sensemaking Visualization Tool with Military Doctrinal Elements
In: DTIC (2008)
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20
Automation Reliability in Unmanned Aerial Vehicle Control: A Reliance-Compliance Model of Automation Dependence in High Workload
In: DTIC (2006)
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