... Graph-based Ranking Algorithms for Sentence Extraction,
Applied to Text Summarization
Rada Mihalcea
Department of Computer Science
University ... represents the text, and intercon-
nects words or other text entities with meaningful re-
lations. For the task of sentence extraction, the goal
is to rank entire sentences, and therefore a vertex ... from a sentence to...
... correct
tree for that sentence.
We assume some way of enumerating a set of
candidates for a particular sentence. We use to
denote the
’th candidate for the ’th sentence in
training data, and to denote
the ... parameters
For For
If Then If Then
Output on test sentence : Output on test sentence :
.
Figure 1: a) The perceptron algorithm for ranking problems. b) The algor...
... and SVMs, and the re -ranking
models (RR) applied to FST. A, B and C refer
to the three approaches for generating training in-
stances described above. As already mentioned
for these large datasets, ... performs the task of translating
a spoken sentence into its meaning representation
based on semantic constituents. These are the
units for meaning representation and are often r...
...
1996), incorporating information gained from the
textual context of the candidate term.
2
Context information
for terms
The idea of incorporating context information for
term extraction came ... context carries information about terms it
should be involved in the procedure for their ex-
traction. We incorporate context information in the
form of weights constructed in a fully a...
... the next
section.
contains a dictionary of atomic formulas that spec-
ifies which input atomic formulas can be translated
into which output atomic formulas.
Existential equivalences in KLDT's ... input language.
We assume that each atomic formula with input
predicates can be translated into an atomic formula
with output predicates. An RLDT therefore also
aThe predicate
unknown...
... defined for improv-
ing the tagging accuracy. However, to conform to
the constraints of closed test in Bakeoff 2005, some
features, such as syntactic information and character
encodings for numbers ... used
for re-segmentation. For the subword-based IOB
tagging, we need to add some multiple-character
words into the lexicon subset. Since it is hard to
decide the optimal number o...
... of Information Extraction (IE) is to dis-
cover relevant segments of information in a data
stream that will be useful for structuring the data.
In the case of text, this usually amounts to finding
mentions ... to map arbitrary ob-
jects to a Euclidian feature space. Haussler (1999)
describes a framework for calculating kernels over
discrete structures such as strings and trees. St...
... cor-
pus. The scores indicate the potential for a can-
didate to be a collocation. They can be used for
ranking (candidates with high scores at the top),
or for classification (by setting a threshold ... (5 units) with 82 predictors
NNet (5 units) with 42 predictors
NNet (5 units) with 17 predictors
NNet (5 units) with 7 predictors
Cosine context similarity in boolean vector space (7...
... the-of
of-but for- but but-but said-said to- of the-a
in-but was-but it-but a-and a-the of-the
to- but that-but the-it* to- and to- to the-in
and-but but-the to- it* and-and the-the in-in
a-but he-but said-in to- the ... to 2%
for Comparison, and 6% for Contingency.
7.3 Best results
Adding other features to word pairs leads to im-
proved performance for Contingency, Expansi...
... factor, HSF1. Proc Natl Acad Sci USA 88,
6906–6910.
21 Schuetz TJ, Gallo GJ, Sheldon L, Tempst P & Kings-
ton RE (1991) Isolation of a cDNA for HSF2: evi-
dence for two heat shock factor ... shock factor family and adaptation to
proteotoxic stress
Mitsuaki Fujimoto and Akira Nakai
Yamaguchi University School of Medicine, Ube, Japan
Introduction
All living organisms respond to elev...