Search Results for author: Mark Last

Found 13 papers, 0 papers with code

An Interactive Analysis of User-reported Long COVID Symptoms using Twitter Data

no code implementations WIT (ACL) 2022 Lin Miao, Mark Last, Marina Litvak

With millions of documented recoveries from COVID-19 worldwide, various long-term sequelae have been observed in a large group of survivors.

Pattern Recognition in Vital Signs Using Spectrograms

no code implementations5 Aug 2021 Sidharth Srivatsav Sribhashyam, Md Sirajus Salekin, Dmitry Goldgof, Ghada Zamzmi, Mark Last, Yu Sun

The results from the proposed approach are promising with an accuracy of 91. 55% and 91. 67% in prediction and classification tasks respectively.

Time Series Time Series Analysis

Detecting Troll Tweets in a Bilingual Corpus

no code implementations LREC 2020 Lin Miao, Mark Last, Marina Litvak

This paper aims to detect troll tweets in both English and Russian assuming that the tweets are generated by some {``}troll farm.

Authorship Verification Feature Engineering +3

Parallel 3DPIFCM Algorithm for Noisy Brain MRI Images

no code implementations5 Feb 2020 Arie Agranonik, Maya Herman, Mark Last

We show that the speedup of the parallel version increases as we increase the size of the image due to better utilization of cores in the GPU.

3DPIFCM Novel Algorithm for Segmentation of Noisy Brain MRI Images

no code implementations5 Feb 2020 Arie Agranonik, Maya Herman, Mark Last

We present a novel algorithm named 3DPIFCM, for automatic segmentation of noisy MRI Brain images.

Segmentation

Using Discretization for Extending the Set of Predictive Features

no code implementations9 Feb 2018 Avi Rosenfeld, Ron Illuz, Dovid Gottesman, Mark Last

We also demonstrate that $ 10 $ other discretization algorithms can also be used to generate features that yield improved performance when used in combination with the original non-discretized data.

Attribute

A Syntactic Approach to Domain-Specific Automatic Question Generation

no code implementations28 Dec 2017 Guy Danon, Mark Last

Contrary to existing domain-specific AQG systems that utilize the template-based approach to question generation, we propose to transform each source sentence into a set of questions by applying a series of domain-independent rules (a syntactic-based approach).

Question Answering Question Generation +2

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