Точность предсказания

We examine the utility of multiple types of turn-level and contextual linguistic features for automatically predicting student emotions in human-human spoken tutoring dialogues. We first annotate student turns in our …...

We present a novel method for predicting in- flected word forms for generating morpho- logically rich languages in machine trans- lation. We utilize a rich set of syntactic and morphological …...

. As previous word adoption models, though proposing potential factors that influence the survival of neologisms, receive little empirical examination, this corpus-based study compares the performance of two such models …...

The work presented in this paper explores a supervised method for learning a prob- abilistic model of a lexicon of VerbNet classes. We intend for the probabilis- tic model to …...

Determining the reading level of children’s lit- erature is an important task for providing edu- cators and parents with an appropriate reading trajectory through a curriculum. Automating this process has …...

We present the results of several machine learning tasks designed to predict rhetori- cal relations that hold between clauses in discourse. We demonstrate that organizing rhetorical relations into different granularity …...

This study focuses on modeling discourse co- herence in the context of automated assess- ment of spontaneous speech from non-native speakers. Discourse coherence has always been used as a key …...

In this paper, we present a recursive neural network (RNN) model that works on a syn- tactic tree. Our model differs from previous RNN models in that the model allows …...

AbstractWe investigate the importance of text analysis for stock price prediction. In particular, we introduce a system that forecasts companies’ stock price changes (UP, DOWN, STAY) in response to financial …...

AbstractAspect-level analysis of sentiments contained in a review text is important to reveal a detailed picture of consumer opinions. While a plethora of methods have been traditionally employed for this …...

AbstractIn order to organize the large number of products listed in e-commerce sites, each product is usually assigned to one of the multi-level categories in the taxonomy tree. It is …...

AbstractMuch of our online communication is text-mediated and, lately, more common with automated agents. Unlike interacting with humans, these agents currently do not tailor their language to the type of …...

AbstractMany natural and formal languages contain words or symbols that require a matching counterpart for making an expression well-formed. The combination of opening and closing brackets is a typical example …...

In this paper, the problem of recovery of morphological information lost in abbreviated forms is addressed with a focus on highly inflected languages. Evidence is presented that the correct inflected …...

AbstractThis paper presents a new resource for automatically assessing text difficulty in the context of Italian as a second or foreign language learning and teaching. It is called MALT-IT2, and …...

AbstractPeople vary in their ability to make accurate predictions about the future. Prior studies have shown that some individuals can predict the outcome of future events with consistently better accuracy. …...

AbstractHealthcare predictive analytics aids medical decision-making, diagnosis prediction and drug review analysis. Therefore, prediction accuracy is an important criteria which also necessitates robust predictive language models. However, the models using …...

AbstractAdversarial attacks alter NLP model predictions by perturbing test-time inputs. However, it is much less understood whether, and how, predictions can be manipulated with small, concealed changes to the training …...

AbstractTransformer-based pre-trained language models have significantly improved the performance of various natural language processing (NLP) tasks in the recent years. While effective and prevalent, these models are usually prohibitively large …...