COLING
2008
14 years 1 months ago
2008
The originality of this work leads in tackling text compression using an unsupervised method, based on a deep linguistic analysis, and without resorting on a learning corpus. This...
COLING
2008
14 years 1 months ago
2008
We present SMMR, a scalable sentence scoring method for query-oriented update summarization. Sentences are scored thanks to a criterion combining query relevance and dissimilarity...
COLING
2008
14 years 1 months ago
2008
Computing the similarity between entities is a core component of many NLP tasks such as measuring the semantic similarity of terms for generating a distributional thesaurus. In th...
COLING
2008
14 years 1 months ago
2008
This paper elaborates a model for representing semantic calendar expressions (SCEs), which correspond to the intensional meanings of natural-language calendar phrases. The model u...
COLING
2008
14 years 1 months ago
2008
This paper studies the role of base-NP information in dependency parsing for Thai. The baseline performance reveals that the base-NP chunking task for Thai is much more difficult ...
COLING
2008
14 years 1 months ago
2008
It is shown how weighted context-free grammars can be used to recognize languages beyond their weak generative capacity by a one-step constant time extension of standard recogniti...
COLING
2008
14 years 1 months ago
2008
This work presents the development of a system that detects incorrect uses of complex postpositions in Basque, an agglutinative language. Error detection in complex postpositions ...
COLING
2008
14 years 1 months ago
2008
In this paper we propose a new distance function (rank distance) designed to reflect stylistic similarity between texts. To assess the ability of this distance measure to capture ...
COLING
2008
14 years 1 months ago
2008
Treating classification as seeking minimum cuts in the appropriate graph has proven effective in a number of applications. The power of this approach lies in its ability to incorp...
COLING
2008
14 years 1 months ago
2008
Recent years have witnessed a growing interest in analogical learning for NLP applications. If the principle of analogical learning is quite simple, it does involve complex steps ...