Papers Intent Classification
“Intent Classification” 태그가 달린 논문 375편 · 필터 해제
Joint Modelling of Cyber Activities and Physical Context to Improve Prediction of Visitor Behaviors
This paper investigates the Cyber-Physical behavior of users in a large indoor shopping mall by leveraging anonymized (opt in) Wi-Fi association and browsing logs recorded by the mall operators. Our analysis shows that m…
intent-classificationIntent ClassificationData balancing for boosting performance of low-frequency classes in Spoken Language Understanding
Despite the fact that data imbalance is becoming more and more common in real-world Spoken Language Understanding (SLU) applications, it has not been studied extensively in the literature. To the best of our knowledge, t…
intent-classificationIntent ClassificationIntent Classification and Slot Fillingslot-filling+2Improving End-to-End Speech-to-Intent Classification with Reptile
End-to-end spoken language understanding (SLU) systems have many advantages over conventional pipeline systems, but collecting in-domain speech data to train an end-to-end system is costly and time consuming. One questio…
ClassificationGeneral Classificationintent-classificationIntent Classification+4KBot: a Knowledge graph based chatBot for natural language understanding over linked data
With the rapid progress of the semantic web, a huge amount of structured data has become available on the web in the form of knowledge bases (KBs). Making these data accessible and useful for end-users is one of the main…
Chatbotintent-classificationIntent ClassificationNatural Language UnderstandingLeveraging Adversarial Training in Self-Learning for Cross-Lingual Text Classification
In cross-lingual text classification, one seeks to exploit labeled data from one language to train a text classification model that can then be applied to a completely different language. Recent multilingual representati…
ClassificationGeneral Classificationintent-classificationIntent Classification+3Unknown Intent Detection Using Gaussian Mixture Model with an Application to Zero-shot Intent Classification
User intent classification plays a vital role in dialogue systems. Since user intent may frequently change over time in many realistic scenarios, unknown (new) intent detection has become an essential problem, where the …
ClassificationGeneral Classificationintent-classificationIntent Classification+3Improving Intent Classification in an E-commerce Voice Assistant by Using Inter-Utterance Context
In this work, we improve the intent classification in an English based e-commerce voice assistant by using inter-utterance context. For increased user adaptation and hence being more profitable, an e-commerce voice assis…
ClassificationGeneral Classificationintent-classificationIntent ClassificationA Study on the Influence of Architecture Complexity of RNNs for Intent Classification in E-Commerce Chats in Bahasa Indonesia
We present our work in the intent classification of chat utterances. We use several recurrent neural network (RNN) architectures of different complexity levels; basic RNN, GRU, LSTM, and BiLSTM. Experiments are performed…
intent-classificationIntent ClassificationIIT Gandhinagar at SemEval-2020 Task 9: Code-Mixed Sentiment Classification Using Candidate Sentence Generation and Selection
Code-mixing is the phenomenon of using multiple languages in the same utterance of a text or speech. It is a frequently used pattern of communication on various platforms such as social media sites, online gaming, produc…
Humor Detectionintent-classificationIntent ClassificationSentence+2Chatbot: A Conversational Agent employed with Named Entity Recognition Model using Artificial Neural Network
Chatbot is a technology that is used to mimic human behavior using natural language. There are different types of Chatbot that can be used as conversational agent in various business domains in order to increase the cust…
ChatbotInformation Retrievalintent-classificationIntent Classification+7User Intent Inference for Web Search and Conversational Agents
User intent understanding is a crucial step in designing both conversational agents and search engines. Detecting or inferring user intent is challenging, since the user utterances or queries can be short, ambiguous, and…
General Classificationintent-classificationIntent ClassificationNatural Language UnderstandingLearning with Weak Supervision for Email Intent Detection
Email remains one of the most frequently used means of online communication. People spend a significant amount of time every day on emails to exchange information, manage tasks and schedule events. Previous work has stud…
intent-classificationIntent ClassificationIntent DetectionSchedulingImpactCite: An XLNet-based method for Citation Impact Analysis
Citations play a vital role in understanding the impact of scientific literature. Generally, citations are analyzed quantitatively whereas qualitative analysis of citations can reveal deeper insights into the impact of a…
Citation Intent ClassificationClassificationGeneral Classificationintent-classification+3MTSI-BERT: A Session-aware Knowledge-based Conversational Agent
In the last years, the state of the art of NLP research has made a huge step forward. Since the release of ELMo (Peters et al., 2018), a new race for the leading scoreboards of all the main linguistic tasks has begun. Se…
Chatbotintent-classificationIntent Classificationnamed-entity-recognition+5Building a Task-oriented Dialog System for Languages with no Training Data: the Case for Basque
This paper presents an approach for developing a task-oriented dialog system for less-resourced languages in scenarios where training data is not available. Both intent classification and slot filling are tackled. We pro…
ClassificationGeneral Classificationintent-classificationIntent Classification+6Data Query Language and Corpus Tools for Slot-Filling and Intent Classification Data
Typical machine learning approaches to developing task-oriented dialog systems require the collection and management of large amounts of training data, especially for the tasks of intent classification and slot-filling. …
ClassificationGeneral Classificationintent-classificationIntent Classification+4End-to-End Slot Alignment and Recognition for Cross-Lingual NLU
Natural language understanding (NLU) in the context of goal-oriented dialog systems typically includes intent classification and slot labeling tasks. Existing methods to expand an NLU system to new languages use machine …
Cross-Lingual TransferGoal-Oriented Dialogintent-classificationIntent Classification+4Learning to Classify Intents and Slot Labels Given a Handful of Examples
Intent classification (IC) and slot filling (SF) are core components in most goal-oriented dialogue systems. Current IC/SF models perform poorly when the number of training examples per class is small. We propose a new f…
Few-Shot LearningGoal-Oriented Dialogue Systemsintent-classificationIntent Classification+3A Financial Service Chatbot based on Deep Bidirectional Transformers
We develop a chatbot using Deep Bidirectional Transformer models (BERT) to handle client questions in financial investment customer service. The bot can recognize 381 intents, and decides when to say "I don't know" and e…
Chatbotintent-classificationIntent ClassificationLanguage Modeling+2Intent Classification in Question-Answering Using LSTM Architectures
Question-answering (QA) is certainly the best known and probably also one of the most complex problem within Natural Language Processing (NLP) and artificial intelligence (AI). Since the complete solution to the problem …
ClassificationGeneral Classificationintent-classificationIntent Classification+1