Binary Classifiers

This paper compares a range of methods for classifying words based on linguis- tic diagnostics, focusing on the task of learning countabilities for English nouns. We propose two basic approaches …...

We develop a data set of Malay lexemes la- belled with count classifiers, that are attested in raw or lemmatised corpora. A maximum entropy classifier based on simple, language- inspecific …...

A machine learning mechanism is learned from human annotations in order to perform preference ranking. The mechanism operates on a sentence level and ranks the alternative machine translations of each …...

We describe the Heidelberg University system for the Cross-lingual Textual Entailment task at SemEval-2012. The system relies on fea- tures extracted with statistical machine trans- lation methods and tools, combining …...

The emergence of dialogue on social medial neccessitates the development of new dialogue processing models. We argue that to address coherence and to infer the implicatures of social dialogue it …...

This paper describes our system used in the Aspect Based Sentiment Analysis Task 12 of SemEval-2015. Our system is based on two supervised machine learning algorithms: sig- moidal feedforward network …...

AbstractResponse selection plays a vital role in building retrieval-based conversation systems. Despite that response selection is naturally a learning-to-rank problem, most prior works take a point-wise view and train binary …...

Discovering whether words are semantically related and identifying the specific semantic re- lation that holds between them is of crucial im- portance for automatic reasoning on text data. For that …...