CrossValidation

We predict discourse segment boundaries from linguistic features of utterances, using a corpus of spoken narratives as data. We present two methods for developing seg- mentation algorithms from training data: …...

In a language generation system, a content planner embodies one or more “plans” that are usually hand–crafted, sometimes through manual analysis of target text. In this paper, we present a …...

Our group participated in the Basque and En- glish lexical sample tasks in Senseval-3. language-specific feature set was defined forA Basque. Four different learning algorithms were applied, and also a …...

Research on document similarity has shown that complex representations are not more accurate than the simple bag-of- words. Term clustering, e.g. using latent semantic indexing, word co-occurrences or synonym relations …...

We describe an implementation of data- driven selection of emphatic facial dis- plays for an embodied conversational agent in a dialogue system. A corpus of sentences in the domain of …...

Named Entity Recognition (NER) is a fundamental task in text mining and nat- ural language understanding. Current ap- proaches to NER (mostly based on super- vised learning) perform well on …...

Frequency distribution models tuned to words and other linguistic events can pre- dict the number of distinct types and their frequency distribution in samples of arbi- trary sizes. We conduct, …...

This paper describes the supervised ac- quisition of semantic event frames based on a corpus of biomedical abstracts, in which the biological process of E. coli gene regulation has been …...

AbstractIn this paper, we report on the design of a part-of-speech-tagset for Wolof and on the creation of a semi-automatically annotated gold standard. In order to achieve high-quality annotation relatively …...

Machine translation (MT) technology is becoming more and more pervasive, yet the quality of MT output is still not ideal. Thus, human corrections are used to edit the output for …...

Previous approaches to the task of native language identification (Koppel et al., 2005) have been limited to small, within-corpus evaluations. Because these are restrictive and unreliable, we apply cross-corpus evaluation …...

AbstractWe attempt to identify citations in non-academic text such as patents. Unlike academic articles which often provide bibliographies and follow consistent citation styles, non-academic text cites scientific research in a …...

The current paper proposes a novel approach to Spanish zero pronoun resolution in the context of Spanish to Korean Machine Translation (MT). Spanish is one of the well-known 'pro-drop' languages …...

This paper presents a method to predict re- trieval terms from relevant/surrounding words or descriptive texts in Japanese by using deep belief networks (DBN), one of two typical types of …...

Analyzing arguments in user-generated Web discourse has recently gained atten- tion in argumentation mining, an evolving field of NLP. Current approaches, which employ fully-supervised machine learn- ing, are usually domain …...

In this paper, we describe our approach to Se- meval 2015 task 10 subtask B, message level sentiment detection. Our system implements a variety of classifiers and data preparation tech- …...

Our purpose is to use Twitter data to infer per- sonal values in marketing for Japanese con- sumers. In this paper, we reintroduce our per- sonal value system and apply …...

 Korean is one of the well-known „pro-drop‟ languages. When translating Korean zero object into languages in which objects have to be overtly expressed, the resolution of zero object is …...

AbstractIn this paper, we present a study on tweet classification which aims to define the communication behavior of the 103 French museums that participated in 2014 in the Twitter operation: …...

AbstractWe investigate using Adaptor Grammars for unsupervised morphological segmentation. Using six development languages, we investigate in detail different grammars, the use of morphological knowledge from outside sources, and the use …...

Under the issue of gender and Natural Language Processing (NLP), most papers aim at gender- norm language that spoken by biologically males and females with opposite-sex desires. However, from the …...

AbstractThis paper discusses the experiments performed for predicting the emotion intensity in tweets using a generalized supervised learning approach. We extract 3 kind of features from each of the tweets …...

AbstractWe investigate the stability of narrative schemas (Chambers and Jurafsky, 2009) automatically induced from a news corpus, representing recurring narratives in a corpus. If such techniques produce meaningful results, we …...

AbstractThe goal of this paper is to use all available Polish language data sets to seek the best possible performance in supervised sentiment analysis of short texts. We use text …...

In this paper, we conducted an aspect-based sentiment analysis using Google Maps user reviews of Indonesia’s tourism destinations which are Borobudur and Prambanan Temple. The aspects we used are Attractions, …...

AbstractThe recent algorithms for math word problems (MWP) neglect to use outside knowledge not present in the problems. Most of them only capture the word-level relationship and ignore to build …...

Abstract“Medical named entity recognition (NER), a fundamental task of medical information extraction, is crucial for medical knowledge graph construction, medical question answering, and automatic medical record analysis, etc. Compared with …...

AbstractSynonym and antonym practice are the most common practices in our early childhood. It correlated our known words to a better place deep in our intuition. At the beginning of …...