Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Estimation of Individual Micro Data from Aggregated Open Data   In this paper, we propose a method of estimating individual micro data from
aggregated open data based on semi-supervised learning and conditional
probability. Firstly, the proposed method collects aggregated open data and
support data, which are related to the individual micro data to be estimated.
Then, we perform the locality sensitive hashing (LSH) algorithm to find a
subset of the support data that is similar to the aggregated open data and then
classify them by using the Ensemble classification model, which is learned by
semi-supervised learning. Finally, we use conditional probability to estimate
the individual micro data by finding the most suitable record for the
probability distribution of the individual micro data among the classification
results. To evaluate the performance of the proposed method, we estimated the
individual building data where the fire occurred using the aggregated fire open
data. According to the experimental results, the micro data estimation
performance of the proposed method is 59.41% on average in terms of accuracy.

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The categories of this paper are: alg-geom
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The categories of this paper are: bayes-an
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The categories of this paper are: q-alg
12
The categories of this paper are: nucl-th
4
The categories of this paper are: cond-mat
22
The categories of this paper are: chao-dyn
24
The categories of this paper are: dg-ga
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The categories of this paper are: chem-ph
29
The categories of this paper are: funct-an
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The categories of this paper are: supr-con
11
The categories of this paper are: hep-lat
32
The categories of this paper are: atom-ph
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The categories of this paper are: eess
6
The categories of this paper are: astro-ph
17
The categories of this paper are: q-fin
18
The categories of this paper are: econ