Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Towards Building a Knowledge Base of Monetary Transactions from a News
  Collection   We address the problem of extracting structured representations of economic
events from a large corpus of news articles, using a combination of natural
language processing and machine learning techniques. The developed techniques
allow for semi-automatic population of a financial knowledge base, which, in
turn, may be used to support a range of data mining and exploration tasks. The
key challenge we face in this domain is that the same event is often reported
multiple times, with varying correctness of details. We address this challenge
by first collecting all information pertinent to a given event from the entire
corpus, then considering all possible representations of the event, and
finally, using a supervised learning method, to rank these representations by
the associated confidence scores. A main innovative element of our approach is
that it jointly extracts and stores all attributes of the event as a single
representation (quintuple). Using a purpose-built test set we demonstrate that
our supervised learning approach can achieve 25% improvement in F1-score over
baseline methods that consider the earliest, the latest or the most frequent
reporting of the event.

36
The categories of this paper are: cmp-lg
6
The categories of this paper are: astro-ph
26
The categories of this paper are: bayes-an
9
The categories of this paper are: nlin
18
The categories of this paper are: econ
21
The categories of this paper are: adap-org
0
The categories of this paper are: hep-ph
27
The categories of this paper are: comp-gas
33
The categories of this paper are: plasm-ph
11
The categories of this paper are: hep-lat
19
The categories of this paper are: eess
30
The categories of this paper are: q-alg
35
The categories of this paper are: mtrl-th
20
The categories of this paper are: acc-phys
23
The categories of this paper are: solv-int
29
The categories of this paper are: funct-an