In this work, we present two complementary methods for the expansion of psycholinguistics norms. The first method is a randomtraversal spreading activation approach which transfers existing norms onto semantically related terms using notions of synonymy, hypernymy, and pertainymy to approach full coverage of the English language. The second method makes use of recent advances in distributional ...

This paper introduces a new training set condensation technique designed for mixtures of labeled and unlabeled data. It finds a condensed set of labeled and unlabeled data points, typically smaller than what is obtained using condensed nearest neighbor on the labeled data only, and improves classification accuracy. We evaluate the algorithm on semisupervised part-of-speech tagging and present t...

Semi-leptonic and radiative semi-inclusive decays of heavy mesons are currently under intense investigation. Non perturbative physics seems to be more manageable in such decays, and there is hope for a reduction of theoretical assumptions and a more stringent comparison with experimental data. Several effective approaches to such decays are available. Most commonly, in order to calculate the de...

This paper reports recent efforts to apply the speaker-independent SPHINX-H system to the DARPA Wall Street Journal continuous speech recognition task. In SPHINX-H, we incorporated additional dynamic and speaker-normalized features, replaced discrete models with sex-dependent semi-continuous hidden Markov models, augmented within-word triphones with between-word triphones, and extended generali...

The proposed algorithmic approach deals with finding the sense of a word in an electronic data. Now a day, in different communication mediums like internet, mobile services etc. people use few words, which are slang in nature. This approach detects those abusive words using supervised learning procedure. But in the real life scenario, the slang words are not used in complete word forms always. ...

Random Forest is an ensemble supervised machine learning technique. Machine learning techniques have applications in the area of Data mining. Random Forest has tremendous potential of becoming a popular technique for future classifiers because its performance has been found to be comparable with ensemble techniques bagging and boosting. Hence, an in-depth study of existing work related to Rando...