FeatureExtraction

We describe the University of Maryland's su- pervised sense tagger, which participated in the SENSEVAL-2 lexical sample evaluations for En- glish, Spanish, and Swedish; we also present un- official results …...

Automatic text categorization is a problem of automatically assigning text documents to predefined categories. In order to classify text documents, we must extract good features from them. In previous research, …...

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 …...

Modern statistical machine translation sys- tems may be seen as using two components: feature extraction, that summarizes informa- tion about the translation, and a log-linear framework to combine features. In …...

AbstractWith the growing interest in opinion mining from web data, more works are focused on mining in English and Chinese reviews. Probing into the problem of product opinion mining, this …...

AbstractThe goal of our research is the development of algorithms for automatic estimation of a person's verbal intelligence based on the analysis of transcribed spoken utterances. In this paper we …...

AbstractAnnotation of digitized pages from historical document collections is very important to research on automatic extraction of text blocks, lines, and handwriting recognition. We have recently introduced a new handwritten …...

This paper describes a novel approach aimed to identify a priori which subset of machine translation (MT) systems among a known set will produce the most reliable translations for a …...

The paper describes the method of extraction of two-word domain terms combining their features. The features are computed from three sources: the occurrence statistics in a domain-specific text collection, the …...

Definite Anaphora in Chinese Texts Tyne Liang∗ and Jyun-Hua Cheng∗ Abstract Anaphora is a rhetorical device commonly used in written texts. It denotes the use of terms referring to previously-mentioned …...

AbstractInteractive story systems often involve dialogue with virtual dramatic characters. However, to date most character dialogue is written by hand. One way to ease the authoring process is to (semi-)automatically …...

Automatic methods to create entity dictionaries or gazetteers have used only a small number of entity types (18 at maximum), which could pose a limitation for fine-grained information extraction. This …...

This paper describes the features and the ma- chine learning methods used by Dublin City University (DCU) and SYMANTEC for the WMT 2012 quality estimation task. Two sets of features …...

AbstractReflecting the rapid growth of science, technology, and culture, it has become common practice to consult tools on the World Wide Web for various terms. Existing search engines provide an …...

Citations are a valuable resource for characterizing scientific publications that has already been used in applications such as summarization and information retrieval. These applications could be even better served by …...

AbstractAutomatic annotation of gesture strokes is important for many gesture and sign language researchers. The unpredictable diversity of human gestures and video recording conditions require that we adopt a more …...

Linking name mentions in microblog posts to a knowledge base, namely microblog entity linking, is useful for text mining tasks on mi- croblog. Entity linking in long text has been …...

AbstractWe construct a large corpus of Japanese predicate phrases for synonym-antonym relations. The corpus consists of 7,278 pairs of predicates such as “receive-permission (ACC)” vs. “obtain-permission (ACC)”, in which each …...

AbstractWe present a methodology to analyze the linguistic evolution of scientific registers with data mining techniques, comparing the insights gained from shallow vs. linguistic features. The focus is on selected …...

This paper presents our approach to se- mantic relatedness and textual entailment subtasks organized as task 1 in SemEval 2014. Specifically, we address two ques- tions: (1) Can we solve …...

The state-of-the-art methods used for relation classification are primarily based on statistical ma- chine learning, and their performance strongly depends on the quality of the extracted features. The extracted features …...

This paper describes our submission to Se- mEval2014 Task 9: Sentiment Analysis in Twitter. Our model is primarily a lexi- con based one, augmented by some pre- processing, including detection …...

We present a novel way of extracting fea- tures from short texts, based on the acti- vation values of an inner layer of a deep convolutional neural network. We use …...

The widespread use of deception in online sources has motivated the need for meth- ods to automatically profile and identify deceivers. This work explores deception, gender and age detection in …...

Document sentiment classification is of- ten processed by applying machine learn- ing techniques, in particular supervised learning which consists basically of two major steps: feature extraction and train- ing the …...

This paper describes our sentiment classifica- tion system submitted to SemEval-2015 Task 10. In the message-level polarity classifica- tion subtask, we obtain the highest macro- averaged F1-scores on three out …...

Determining the temporal order of events in a text is difficult. However, it is crucial to the extraction of narratives, plans, and context. We suggest that a simple, estab- lished …...

This paper presents a clustering approach that simultaneously identifies product features and groups them into aspect categories from on- line reviews. Unlike prior approaches that first extract features and then …...

This paper contains the description of our par- ticipation at task 4 (sub-task A, Message Po- larity Classification) of SemEval-2016. Our proposed system consists mainly of three steps. Firstly, the …...

AbstractWhen designing Natural Language Processing (NLP) applications that use Machine Learning (ML) techniques, feature extraction becomes a significant part of the development effort, whether developing a new application or attempting …...

We describe our submission to SemEval2016 Task 4: Sentiment Analysis in Twitter. The proposed system ranked first for the sub- task B. Our system comprises of multiple in- dependent models …...

Semantic deficit is a symptom of language impairment in Alzheimer’s disease (AD). We present a generalizable method for au- tomatic generation of information content units (ICUs) for a picture used …...

AbstractThough feature extraction is a necessary first step in statistical NLP, it is often seen as a mere preprocessing step. Yet, it can dominate computation time, both during training, and …...

Machine translation quality estimation is a challenging task in the WMT evaluation campaign. Feature extrac- tion plays an important role in auto- matic quality estimation, and in this paper, we …...

We introduce Arabic Data Science Toolkit (ADST), a framework for Arabic language feature extraction, designed for data scientists that may not be familiar with Arabic or natural language processing. The …...

AbstractThis paper proposes a novel feature extraction process for SemEval task 3: Irony detection in English tweets. The proposed system incorporates a concatenative featurization of tweet and hashtags, which helps …...

AbstractWe use a broad coverage, linguistically precise English Resource Grammar (ERG) to detect negation scope in sentences taken from pathology reports. We show that incorporating this information in feature extraction …...

AbstractSince the resources of Community Question Answering are abundant and information sharing becomes universal, it will be increasingly difficult to find factual information for questioners in massive messages. SemEval 2019 …...

AbstractCounterfactuals describe events counter to facts and hence naturally involve common sense, knowledge, and reasoning. SemEval 2020 task 5 is focusing on this field. We participate in the subtask 1 …...

AbstractThe Predictor-Estimator framework for quality estimation (QE) is commonly used for its strong performance. Where the predictor and estimator works on feature extraction and quality evaluation, respectively. However, training the …...

AbstractWe describe the Uppsala NLP submission to SemEval-2021 Task 2 on multilingual and cross-lingual word-in-context disambiguation. We explore the usefulness of three pre-trained multilingual language models, XLM-RoBERTa (XLMR), Multilingual BERT …...

AbstractNLP practitioners often want to take existing trained models and apply them to data from new domains. While fine-tuning or few-shot learning can be used to adapt a base model, …...

AbstractA Visual Question Answering (VQA) model processes images and questions simultaneously with rich semantic information. The attention mechanism can highlight fine-grained features with critical information, thus ensuring that feature extraction …...

AbstractIn this paper, we present the participation of the EMBEDDIA team in the SemEval-2022 Task 8 (Multilingual News Article Similarity). We cover several techniques and propose different methods for finding …...

AbstractIn this article, we seek to automatically identify Hungarian patients suffering from mild cognitive impairment (MCI) or mild Alzheimer disease (mAD) based on their speech transcripts, focusing only on linguistic …...

AbstractThe intended sarcasm cannot be understood until the listener observes that the text’s literal meaning violates truthfulness. Consequently, words and meanings play an essential role in specifying sarcasm. Enriched feature …...

AbstractThis paper presents our submission to the WMT 2022 quality estimation shared task and more specifically to the quality prediction sentence-level direct assessment (DA) subtask. We build a multilingual system …...

AbstractThis work is about finding the similarity between a pair of news articles. There are seven different objective similarity metrics provided in the dataset for each pair and the news …...

In this paper, we explore compact convolutional neural networks (CNNs) for end-to-end key- word spotting from raw audio to final recogni- tion results, without using traditional feature extraction based on …...