Papers Suggestion mining
“Suggestion mining” 태그가 달린 논문 32편 · 필터 해제
A Corpus for Suggestion Mining of German Peer Feedback
Peer feedback in online education becomes increasingly important to meet the demand for feedback in large scale classes, such as e.g. Massive Open Online Courses (MOOCs). However, students are often not experts in how to…
Dependency ParsingSentiment AnalysisSuggestion miningTLMOTE: A Topic-based Language Modelling Approach for Text Oversampling
Training machine learning and deep learning models on unbalanced datasets can lead to a bias portrayed by the models towards the majority classes. To tackle the problem of bias towards majority classes, researchers have …
Language ModellingSentiment AnalysisSpam detectionSuggestion miningAspect Oriented Suggestion Extraction from Online Reviews
In the world of business, products need to evolve adjusting to the needs of the customer to ensure customer satisfaction. The abundance of opinionated text on the internet contains suggestions made by users that can be u…
Aspect ExtractionLanguage ModellingSuggestion miningNear-Zero-Shot Suggestion Mining with a Little Help from WordNet
In this work, we explore the constructive side of online reviews: advice, tips, requests, and suggestions that users provide about goods, venues, services, and other items of interest. To reduce training costs and annota…
Suggestion miningYNU-HPCC at SemEval-2020 Task 8: Using a Parallel-Channel Model for Memotion Analysis
In recent years, the growing ubiquity of Internet memes on social media platforms, such as Facebook, Instagram, and Twitter, has become a topic of immense interest. However, the classification and recognition of memes is…
Emotion RecognitionSentiment AnalysisSentiment ClassificationSuggestion miningOpen Domain Suggestion Mining Leveraging Fine-Grained Analysis
Suggestion mining tasks are often semantically complex and lack sophisticated methodologies that can be applied to real-world data. The presence of suggestions across a large diversity of domains and the absence of large…
DiversitySuggestion miningSemEval-2019 Task 9: Suggestion Mining from Online Reviews and Forums
We present the pilot SemEval task on Suggestion Mining. The task consists of subtasks A and B, where we created labeled data from feedback forum and hotel reviews respectively. Subtask A provides training and test data f…
Suggestion miningm\_y at SemEval-2019 Task 9: Exploring BERT for Suggestion Mining
This paper presents our system to the SemEval-2019 Task 9, Suggestion Mining from Online Reviews and Forums. The goal of this task is to extract suggestions such as the expressions of tips, advice, and recommendations. W…
Suggestion miningDBMS-KU at SemEval-2019 Task 9: Exploring Machine Learning Approaches in Classifying Text as Suggestion or Non-Suggestion
This paper describes the participation of DBMS-KU team in the SemEval 2019 Task 9, that is, suggestion mining from online reviews and forums. To deal with this task, we explore several machine learning approaches, i.e., …
General ClassificationregressionSuggestion miningDS at SemEval-2019 Task 9: From Suggestion Mining with neural networks to adversarial cross-domain classification
Suggestion Mining is the task of classifying sentences into suggestions or non-suggestions. SemEval-2019 Task 9 sets the task to mine suggestions from online texts. For each of the two subtasks, the classification has to…
domain classificationGeneral ClassificationSuggestion miningWord EmbeddingsHybrid RNN at SemEval-2019 Task 9: Blending Information Sources for Domain-Independent Suggestion Mining
Social media has an increasing amount of information that both customers and companies can benefit from. These social media posts can include Tweets or be in the form of vocalization of complements and complaints (e.g., …
Sentiment AnalysisSuggestion miningINRIA at SemEval-2019 Task 9: Suggestion Mining Using SVM with Handcrafted Features
We present the INRIA approach to the suggestion mining task at SemEval 2019. The task consists of two subtasks: suggestion mining under single-domain (Subtask A) and cross-domain (Subtask B) settings. We used the Support…
Suggestion miningLijunyi at SemEval-2019 Task 9: An attention-based LSTM and ensemble of different models for suggestion mining from online reviews and forums
In this paper, we describe a suggestion mining system that participated in SemEval 2019 Task 9, SubTask A - Suggestion Mining from Online Reviews and Forums. Given some suggestions from online reviews and forums that can…
Suggestion miningNTUA-ISLab at SemEval-2019 Task 9: Mining Suggestions in the wild
As online customer forums and product comparison sites increase their societal influence, users are actively expressing their opinions and posting their recommendations on their fellow customers online. However, systems …
PositionSuggestion miningOleNet at SemEval-2019 Task 9: BERT based Multi-Perspective Models for Suggestion Mining
This paper describes our system partici- pated in Task 9 of SemEval-2019: the task is focused on suggestion mining and it aims to classify given sentences into sug- gestion and non-suggestion classes in do- main specific…
SentenceSuggestion miningSSN-SPARKS at SemEval-2019 Task 9: Mining Suggestions from Online Reviews using Deep Learning Techniques on Augmented Data
This paper describes the work on mining the suggestions from online reviews and forums. Opinion mining detects whether the comments are positive, negative or neutral, while suggestion mining explores the review content f…
Data Augmentationfeature selectionGeneral ClassificationOpinion Mining+1Suggestion Miner at SemEval-2019 Task 9: Suggestion Detection in Online Forum using Word Graph
This paper describes the suggestion miner system that participates in SemEval 2019 Task 9 - SubTask A - Suggestion Mining from Online Reviews and Forums. The system participated in the subtasks A. This paper discusses th…
Suggestion miningTeam Taurus at SemEval-2019 Task 9: Expert-informed pattern recognition for suggestion mining
This paper presents our submissions to SemEval-2019 Task9, Suggestion Mining. Our system is one in a series of systems in which we compare an approach using expert-defined rules with a comparable one using machine learni…
BIG-bench Machine LearningSuggestion miningWUT at SemEval-2019 Task 9: Domain-Adversarial Neural Networks for Domain Adaptation in Suggestion Mining
We present a system for cross-domain suggestion mining, prepared for the SemEval-2019 Task 9: Suggestion Mining from Online Reviews and Forums (Subtask B). Our submitted solution for this text classification problem expl…
Domain AdaptationGeneral ClassificationSuggestion miningtext-classification+2Yimmon at SemEval-2019 Task 9: Suggestion Mining with Hybrid Augmented Approaches
Suggestion mining task aims to extract tips, advice, and recommendations from unstructured text. The task includes many challenges, such as class imbalance, figurative expressions, context dependency, and long and comple…
Machine Reading ComprehensionReading ComprehensionSuggestion miningTranslation