Papers Task 2
“Task 2” 태그가 달린 논문 572편 · 필터 해제
Incorporating Dictionaries into Deep Neural Networks for the Chinese Clinical Named Entity Recognition
Clinical Named Entity Recognition (CNER) aims to identify and classify clinical terms such as diseases, symptoms, treatments, exams, and body parts in electronic health records, which is a fundamental and crucial task fo…
Feature Engineeringnamed-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)+1InfyNLP at SMM4H Task 2: Stacked Ensemble of Shallow Convolutional Neural Networks for Identifying Personal Medication Intake from Twitter
This paper describes Infosys's participation in the "2nd Social Media Mining for Health Applications Shared Task at AMIA, 2017, Task 2". Mining social media messages for health and drug related information has received s…
General ClassificationPharmacovigilanceTask 2Relevance Scoring of Triples Using Ordinal Logistic Classification - The Celosia Triple Scorer at WSDM Cup 2017
In this paper, we report our participation in the Task 2: Triple Scoring of WSDM Cup challenge 2017. In this task, we were provided with triples of "type-like" relations which were given human-annotated relevance scores …
Task 2IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases
This paper presents the IJCNLP 2017 shared task on Dimensional Sentiment Analysis for Chinese Phrases (DSAP) which seeks to identify a real-value sentiment score of Chinese single words and multi-word phrases in the both…
Sentiment AnalysisTask 2THU\_NGN at IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases with Deep LSTM
Predicting valence-arousal ratings for words and phrases is very useful for constructing affective resources for dimensional sentiment analysis. Since the existing valence-arousal resources of Chinese are mainly in word-…
Opinion MiningPOSSentiment AnalysisTask 2LDCCNLP at IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases Using Machine Learning
Sentiment analysis on Chinese text has intensively studied. The basic task for related research is to construct an affective lexicon and thereby predict emotional scores of different levels. However, finite lexicon resou…
BIG-bench Machine LearningSentiment AnalysisTask 2Word EmbeddingsCKIP at IJCNLP-2017 Task 2: Neural Valence-Arousal Prediction for Phrases
CKIP takes part in solving the Dimensional Sentiment Analysis for Chinese Phrases (DSAP) share task of IJCNLP 2017. This task calls for systems that can predict the valence and the arousal of Chinese phrases, which are r…
Sentiment AnalysisTask 2CIAL at IJCNLP-2017 Task 2: An Ensemble Valence-Arousal Analysis System for Chinese Words and Phrases
Sentiment lexicon is very helpful in dimensional sentiment applications. Because of countless Chinese words, developing a method to predict unseen Chinese words is required. The proposed method can handle both words and …
Opinion MiningSentiment AnalysisTask 2Alibaba at IJCNLP-2017 Task 2: A Boosted Deep System for Dimensional Sentiment Analysis of Chinese Phrases
This paper introduces Team Alibaba{'}s systems participating IJCNLP 2017 shared task No. 2 Dimensional Sentiment Analysis for Chinese Phrases (DSAP). The systems mainly utilize a multi-layer neural networks, with multipl…
ClusteringFeature EngineeringPart-Of-Speech TaggingPrediction+2NLPSA at IJCNLP-2017 Task 2: Imagine Scenario: Leveraging Supportive Images for Dimensional Sentiment Analysis
Categorical sentiment classification has drawn much attention in the field of NLP, while less work has been conducted for dimensional sentiment analysis (DSA). Recent works for DSA utilize either word embedding, knowledg…
General ClassificationSentiment AnalysisSentiment ClassificationTask 2NCYU at IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases using Vector Representations
This paper presents two vector representations proposed by National Chiayi University (NCYU) about phrased-based sentiment detection which was used to compete in dimensional sentiment analysis for Chinese phrases (DSACP)…
ClusteringSentiment AnalysisTask 2MainiwayAI at IJCNLP-2017 Task 2: Ensembles of Deep Architectures for Valence-Arousal Prediction
This paper introduces Mainiway AI Labs submitted system for the IJCNLP 2017 shared task on Dimensional Sentiment Analysis of Chinese Phrases (DSAP), and related experiments. Our approach consists of deep neural networks …
PredictionSentiment AnalysisTask 2Word EmbeddingsNCTU-NTUT at IJCNLP-2017 Task 2: Deep Phrase Embedding using bi-LSTMs for Valence-Arousal Ratings Prediction of Chinese Phrases
In this paper, a deep phrase embedding approach using bi-directional long short-term memory (Bi-LSTM) is proposed to predict the valence-arousal ratings of Chinese words and phrases. It adopts a Chinese word segmentation…
Chinese Word SegmentationregressionSentiment AnalysisTask 2NTOUA at IJCNLP-2017 Task 2: Predicting Sentiment Scores of Chinese Words and Phrases
This paper describes the approaches of sentimental score prediction in the NTOU DSA system participating in DSAP this year. The modules to predict scores for words are adapted from our system last year. The approach to p…
BIG-bench Machine LearningSentiment AnalysisTask 2Modeling Information Flow Through Deep Neural Networks
This paper proposes a principled information theoretic analysis of classification for deep neural network structures, e.g. convolutional neural networks (CNN). The output of convolutional filters is modeled as a random v…
ClassificationGeneral ClassificationTask 2Transfer LearningAicyber's System for NLPCC 2017 Shared Task 2: Voting of Baselines
This paper presents Aicyber's system for NLPCC 2017 shared task 2. It is formed by a voting of three deep learning based system trained on character-enhanced word vectors and a well known bag-of-word model.
Deep LearningTask 2Fine-tuning Tree-LSTM for phrase-level sentiment classification on a Polish dependency treebank. Submission to PolEval task 2
We describe a variant of Child-Sum Tree-LSTM deep neural network (Tai et al, 2015) fine-tuned for working with dependency trees and morphologically rich languages using the example of Polish. Fine-tuning included applyin…
General ClassificationSentiment AnalysisSentiment ClassificationTask 2+1Aspect-Based Sentiment Analysis Using a Two-Step Neural Network Architecture
The World Wide Web holds a wealth of information in the form of unstructured texts such as customer reviews for products, events and more. By extracting and analyzing the expressed opinions in customer reviews in a fine-…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Sentiment AnalysisTask 2+2DNN and CNN with Weighted and Multi-task Loss Functions for Audio Event Detection
This report presents our audio event detection system submitted for Task 2, "Detection of rare sound events", of DCASE 2017 challenge. The proposed system is based on convolutional neural networks (CNNs) and deep neural …
Event DetectionTask 2SemEval-2017 Task 2: Multilingual and Cross-lingual Semantic Word Similarity
This paper introduces a new task on Multilingual and Cross-lingual SemanticThis paper introduces a new task on Multilingual and Cross-lingual Semantic Word Similarity which measures the semantic similarity of word pairs …
Information RetrievalMachine TranslationQuestion AnsweringRepresentation Learning+7