Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Computing flood probabilities using Twitter: application to the Houston
  urban area during Harvey   In this paper, we investigate the conversion of a Twitter corpus into
geo-referenced raster cells holding the probability of the associated
geographical areas of being flooded. We describe a baseline approach that
combines a density ratio function, aggregation using a spatio-temporal Gaussian
kernel function, and TFIDF textual features. The features are transformed to
probabilities using a logistic regression model. The described method is
evaluated on a corpus collected after the floods that followed Hurricane Harvey
in the Houston urban area in August-September 2017. The baseline reaches a F1
score of 68%. We highlight research directions likely to improve these initial
results.

20
The categories of this paper are: acc-phys
34
The categories of this paper are: chem-ph
7
The categories of this paper are: hep-th
37
The categories of this paper are: supr-con
11
The categories of this paper are: hep-lat
26
The categories of this paper are: bayes-an
33
The categories of this paper are: plasm-ph
2
The categories of this paper are: math
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
31
The categories of this paper are: ao-sci
0
The categories of this paper are: hep-ph
27
The categories of this paper are: comp-gas
23
The categories of this paper are: solv-int
17
The categories of this paper are: q-fin
5
The categories of this paper are: gr-qc