6 research outputs found
Performance of Opinion Summarization towards Extractive Summarization
Opinion summarization summarizes opinion in texts while extractive summarization summarizes texts without considering opinion in the texts. Can opinion summarization be used to produce a better extractive summary? This paper proposes to determine the effectiveness of opinion summarization generation against extractive text summarization. Sentiment that includes emotion which indicates whether a sentence may be positive, negative or neutral is considered. Sentences that have strong sentiment, either positive or negative are deemed important in text summarization to capture the sentiments in a story text. Thus, a comparative study is conducted on two types of summarizations; opinion summarization using the proposed method, which uses two different sentiment lexicons: VADER and SentiWordNet against extractive summarization using established methods: Luhn, Latent Semantic Analysis (LSA) and LexRank. An experiment was performed on 20 news stories, comparing summaries generated by the proposed opinion summarization method against the summaries generated by established extractive summarization methods. From the experiment, the VADER sentiment analyzer produced the best score of 0.51 when evaluated against the LSA method using ROUGE-1 metric. This implies that opinion summarization converges with extractive summarization
A primer on using mathematics to understand COVID-19 dynamics : modeling, analysis and simulations
The novel coronavirus (COVID-19) pandemic that emerged from Wuhan city in December
2019 overwhelmed health systems and paralyzed economies around the world. It became
the most important public health challenge facing mankind since the 1918 Spanish flu
pandemic. Various theoretical and empirical approaches have been designed and used to
gain insight into the transmission dynamics and control of the pandemic. This study
presents a primer for formulating, analysing and simulating mathematical models for
understanding the dynamics of COVID-19. Specifically, we introduce simple compartmental,
Kermack-McKendrick-type epidemic models with homogeneously- and
heterogeneously-mixed populations, an endemic model for assessing the potential
population-level impact of a hypothetical COVID-19 vaccine. We illustrate how some basic
non-pharmaceutical interventions against COVID-19 can be incorporated into the
epidemic model. A brief overview of other kinds of models that have been used to study
the dynamics of COVID-19, such as agent-based, network and statistical models, is also
presented. Possible extensions of the basic model, as well as open challenges associated
with the formulation and theoretical analysis of models for COVID-19 dynamics, are
suggested.The Simons Foundation and the National Science Foundation.http://www.keaipublishing.com/idmam2022Mathematics and Applied Mathematic
Mathematical assessment of the impact of non-pharmaceutical interventions on curtailing the 2019 novel Coronavirus
A novel Coronavirus pandemic emerged in December of 2019, causing devastating
public health impact across the world. In the absence of a safe and effective
vaccine or antiviral, strategies for mitigating the burden of the pandemic are
focused on non-pharmaceutical interventions, such as social-distancing,
contact-tracing, quarantine, isolation and the use of face-masks in public. We
develop a new mathematical model for assessing the population-level impact of
these mitigation strategies. Simulations of the model, using data relevant to
COVID-19 transmission in New York state and the entire US, show that the
pandemic will peak in mid and late April, respectively. The worst-case scenario
projections for cumulative mortality (based on the baseline levels of
anti-COVID non-pharmaceutical interventions considered in the study) in New
York State and the entire US decrease dramatically by 80% and 64%,
respectively, if the strict social-distancing measures implemented are
maintained until the end of May or June, 2020. This study shows that early
termination of strict social-distancing could trigger a devastating second wave
with burden similar to that projected before the onset of strict
social-distance. The use of efficacious face-masks (efficacy greater than 70%)
could lead to the elimination of the pandemic if at least 70% of the residents
of New York state use such masks consistently (nationwide, a compliance of at
least 80% will be required using such masks). The use of low efficacy masks,
such as cloth masks (of efficacy less than 30%), could also lead to significant
reduction of COVID-19 burden (albeit, they are not able to lead to
elimination). Combining low efficacy masks with improved levels of other
anti-COVID-19 intervention measures can lead to elimination of the pandemic.
The mask coverage needed to eliminate COVID-19 decreases if mask-use is
combined with strict social-distancing
Mathematical assessment of the impact of non-pharmaceutical interventions on curtailing the 2019 novel Coronavirus
Please read abstract in the article.The Simons Foundation and the National Science Foundation.http://www.elsevier.com/locate/mbshj2021Mathematics and Applied Mathematic