priority questions of genetics, incubation, treatment, 23 symptoms, and prevention of COVID-19? 24 2. How to extract valued information such as information 25 with authority, insights and innovation for combating 26 SARS-Cov-2? What is the authoritative information and 27 insightful information? 28 3. What are the timelines of themes and topics across all 29 the research literature? 30 We show LLA that integrates text and data mining into a 31 single platform so that insights from data can be visualized, 32 and validated to answer the high-priority questions. applications. Emerging and anomalous information is important 52 for looking for insights and innovation. In paper, we show how to 53 apply game-theoretic framework of lexical link analysis (LLA) to 54 discover and rank high-value information from unstructured and 55 structured data from SARS-Cov-2.
In LLA, a complex system can be expressed in a list of attributes 57 or word features with specific vocabularies or lexicon terms to 58 describe its characteristics. LLA is first a data-driven text analysis 59 method. Fig. 1 shows an example of extracting and learning word Bi-gram also allows LLA to be extended to structured data (15) 70 including meta-data such as the ones for CORD-19, where a word 71
In this paper, we show how to apply an unique information mining method lexical link analysis (LLA) to link unstructured (CORD-19) and structured (Next Strain) data sets to relevant publications, integrate text and data mining into a single platform to discover the insights that can be visualized, and validated to answer the high-priority questions of genetics, incubation, treatment, symptoms, and prevention of COVID-19.
is an attribute combined with its possible values. LLA is related However, the uniqueness of LLA is that we consider anomalous 81 information (word features) might be more interesting. Community 82 detection algorithms have been illustrated by Newman (11, 12) 83 in terms of a quality function as the "modularity" measure for a 84 community (cluster) and optimized using a dendrogram-like greedy America, and 15 cases in Australia.
• Among the four cases of Clade A2, A2a in China, three were 160 collected from 1/28/2020 to 2/6/2020, they were submitted based on these themes. Fig. 8 shows a popular theme of word pair 175 appeared in both data sources. Fig. 9, Fig. 10 , and Fig. 11 show 176 examples of emerging themes appeared in both data sources. Fig. 12 177 shows an example of an anomalous theme appeared in both data 178 sources. Emerging themes are interesting topics for researchers to 179 drill down and discover information in CORD-19 pertinent to high-180 priority questions of the SARS-Cov-2 of genetics (Group 423(E)), 181 tests (Group 50(E)), and prevention (Group 42(E)).
Conclusion and Challenge to Future. We applied an unique 183 information mining method lexical link analysis to conduct a 184 preliminary study to the call to action and help the science 185 