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We present a statistical parsing framework for sentence-level sentiment classification in this article. Unlike previous works that use syntactic parsing results for sentiment analysis, we develop a st...
This paper focuses on a well-known open issue in Semantic Role Classification (SRC) research: the limited influence and sparseness of lexical features. We mitigate this problem using models that integ...
With the increasing rate of patent application filings, automated patent classification is of rising economic importance. This article investigates how patent classification can be improved by using d...
We present a study on the automatic acquisition of semantic classes for Catalan adjectives from distributional and morphological information, with particular emphasis on polysemous adjectives. The aim...
The lack of reliable Chinese sentiment resources limits research progress on Chinese sentiment classification. However, there are many freely available English sentiment resources on the Web. This art...
Aspectual classification maps verbs to a small set of primitive categories in order to reason abouttime. This classification is necessary for interpreting temporal modifiers and assessing temporal rel...
We investigate the problem of binary text classification in the domain of legal docket entries.This work presents an illustrative instance of a domain-specific problem where the stateof-the-art Machin...
In this paper we present a hierarchical large-margin Gaussian mixture modeling framework and evaluate it on the task of phonetic classification. A two-stage hierarchical classifier is trained by alter...
We perform phonetic classiſcation with an architecture whose elements are binary classiſers trained via linear regularized least squares (RLS). RLS is a simple yet powerful regularization al...
Although wavelet analysis has been proposed for speech processing as an alternative to Fourier analysis, most approaches make use of off-the-shelf wavelets and dyadic tree-structured filter banks. In ...
In this paper, we present a wavelet and filter bank framework for context-independent phonetic classification with the aim of extending the work towards a full speech recognition system. The framework...
In this paper we describe our recent efforts to improve acousticphonetic modeling by developing sets of heterogeneous, phoneclass-specific measurements, and combining these diverse measurements into a...
Convolution kernels support the modeling of complex syntactic information in machine-learning tasks. However, such models are highly sensitive to the type and size of syntac-tic structure used. It is ...
Relevance Theory pictures communication as an inferential activity that adjusts, in parallel, the explicit content of utterances, the implicated premises and conclusions that can be derived, and the r...

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