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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 6 of 6 1 Leveraging Lexical Link Analysis (LLA) to discover new knowledge Zhao, Ying; Mackinnon, Douglas J.; Gallup, Shelley P.. - : The Journal of the Military Cyber Professionals Association, 2016 BASE Show details 2 Functional Anatomy of Recognition of Chinese Multi-Character Words: Convergent Evidence from Effects of Transposable Nonwords, Lexicality, and Word Frequency Yu, Xi; Lin, Nan; Zhang, Mingxia. - : Public Library of Science, 2016 BASE Show details 3 Diabetes and Hypertension Consistently Predict the Presence and Extent of Coronary Artery Calcification in Symptomatic Patients: A Systematic Review and Meta-Analysis Nicoll, Rachel; Zhao, Ying; Ibrahimi, Pranvera. - : MDPI, 2016 BASE Show details 4 Leveraging Lexical Link Analysis (LLA) To Discover New Knowledge Zhao, Ying; MacKinnon, Douglas J.; Gallup, Shelley P.; Billingsley, Joseph L. In: Military Cyber Affairs (2016) Abstract: Lexical Link Analysis (LLA) is a form of text mining in which word meanings represented in lexical terms (e.g., word pairs) are treated as if they are in a community of a word network. LLA can provide automated awareness for analyzing text data and reveal previously unknown, data-driven themed connections. We applied LLA to develop authentic archetypes and conversely determine potential imposters of that same archetype. We use publically available social media data to develop a cyber professional as an example. This paper reports the development of the algorithm, the collection and labeling of data, as well as the results of analysis of the characteristics of three authentic cyber professionals using data collected from Facebook, LinkedIn and Twitter. This method can provide automated analyzing and understanding massive Big Data in open and social media data sources to discover new knowledge for a widening range of applications. Keyword: authenticity; big data; collaborative learning agents; Communication Technology and New Media; Computational Engineering; Computer Engineering; cyber professionals; deep learning; lexical link analysis; open source; persona archetype; social media; text mining; unstructured data URL: https://digitalcommons.usf.edu/cgi/viewcontent.cgi?article=1015&context=mca https://digitalcommons.usf.edu/mca/vol2/iss1/3 BASE Hide details 5 Cis-regulatory architecture of a brain-signaling center predates the origin of chordates Yao, Yao; Minor, Paul J.; Zhao, Ying-Tao. - 2016 BASE Show details 6 Functional Anatomy of Recognition of Chinese Multi-Character Words: Convergent Evidence from Effects of Transposable Nonwords, Lexicality, and Word Frequency Lin, Nan; Yu, Xi; Zhao, Ying. - : Public Library of Science, 2016 BASE Show details

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