Papers Intent Classification
“Intent Classification” 태그가 달린 논문 375편 · 필터 해제
Joint Multiple Intent Detection and Slot Labeling for Goal-Oriented Dialog
Neural network models have recently gained traction for sentence-level intent classification and token-based slot-label identification. In many real-world scenarios, users have multiple intents in the same utterance, and…
General ClassificationGoal-Oriented Dialogintent-classificationIntent Classification+4Submodular Optimization-based Diverse Paraphrasing and its Effectiveness in Data Augmentation
Inducing diversity in the task of paraphrasing is an important problem in NLP with applications in data augmentation and conversational agents. Previous paraphrasing approaches have mainly focused on the issue of generat…
Data AugmentationDiversityintent-classificationIntent ClassificationOutlier Detection for Improved Data Quality and Diversity in Dialog Systems
In a corpus of data, outliers are either errors: mistakes in the data that are counterproductive, or are unique: informative samples that improve model robustness. Identifying outliers can lead to better datasets by (1) …
Diversityintent-classificationIntent ClassificationIntent Classification and Slot Filling+5Structural Scaffolds for Citation Intent Classification in Scientific Publications
Identifying the intent of a citation in scientific papers (e.g., background information, use of methods, comparing results) is critical for machine reading of individual publications and automated analysis of the scienti…
ARCCitation Intent ClassificationClassificationGeneral Classification+4Privacy-preserving Active Learning on Sensitive Data for User Intent Classification
Active learning holds promise of significantly reducing data annotation costs while maintaining reasonable model performance. However, it requires sending data to annotators for labeling. This presents a possible privacy…
Active LearningBinary ClassificationGeneral Classificationintent-classification+2Question Embeddings Based on Shannon Entropy: Solving intent classification task in goal-oriented dialogue system
Question-answering systems and voice assistants are becoming major part of client service departments of many organizations, helping them to reduce the labor costs of staff. In many such systems, there is always natural …
General Classificationintent-classificationIntent ClassificationIntent Detection+3Simple, Fast, Accurate Intent Classification and Slot Labeling for Goal-Oriented Dialogue Systems
With the advent of conversational assistants, like Amazon Alexa, Google Now, etc., dialogue systems are gaining a lot of traction, especially in industrial setting. These systems typically consist of Spoken Language unde…
General ClassificationGoal-Oriented Dialogue Systemsintent-classificationIntent Classification+1Benchmarking Natural Language Understanding Services for building Conversational Agents
We have recently seen the emergence of several publicly available Natural Language Understanding (NLU) toolkits, which map user utterances to structured, but more abstract, Dialogue Act (DA) or Intent specifications, whi…
BenchmarkingGeneral Classificationintent-classificationIntent Classification+1BERT for Joint Intent Classification and Slot Filling
Intent classification and slot filling are two essential tasks for natural language understanding. They often suffer from small-scale human-labeled training data, resulting in poor generalization capability, especially f…
General Classificationintent-classificationIntent ClassificationIntent Detection+3Induction Networks for Few-Shot Text Classification
Text classification tends to struggle when data is deficient or when it needs to adapt to unseen classes. In such challenging scenarios, recent studies have used meta-learning to simulate the few-shot task, in which new …
Few-Shot Text ClassificationGeneral Classificationintent-classificationIntent Classification+4Intent Detection and Slots Prompt in a Closed-Domain Chatbot
In this paper, we introduce a methodology for predicting intent and slots of a query for a chatbot that answers career-related queries. We take a multi-staged approach where both the processes (intent-classification and …
ChatbotClassificationDecision MakingGeneral Classification+3Natural language understanding for task oriented dialog in the biomedical domain in a low resources context
In the biomedical domain, the lack of sharable datasets often limit the possibility of developing natural language processing systems, especially dialogue applications and natural language understanding models. To overco…
Data AugmentationGeneral Classificationintent-classificationIntent Classification+4Developing Production-Level Conversational Interfaces with Shallow Semantic Parsing
We demonstrate an end-to-end approach for building conversational interfaces from prototype to production that has proven to work well for a number of applications across diverse verticals. Our architecture improves on t…
Dialogue ManagementGeneral ClassificationIntent ClassificationManagement+3Subword Semantic Hashing for Intent Classification on Small Datasets
In this paper, we introduce the use of Semantic Hashing as embedding for the task of Intent Classification and achieve state-of-the-art performance on three frequently used benchmarks. Intent Classification on a small da…
ChatbotGeneral Classificationintent-classificationIntent Classification+2Adversarial Training for Multi-task and Multi-lingual Joint Modeling of Utterance Intent Classification
This paper proposes an adversarial training method for the multi-task and multi-lingual joint modeling needed for utterance intent classification. In joint modeling, common knowledge can be efficiently utilized among mul…
General Classificationintent-classificationIntent ClassificationSpoken Dialogue SystemsModeling Temporality of Human Intentions by Domain Adaptation
Categorizing patient{'}s intentions in conversational assessment can help decision making in clinical treatments. Many conversation corpora span broaden a series of time stages. However, it is not clear that how the them…
Decision MakingDomain AdaptationGeneral ClassificationIntent Classification+1DeepPavlov: Open-Source Library for Dialogue Systems
Adoption of messaging communication and voice assistants has grown rapidly in the last years. This creates a demand for tools that speed up prototyping of feature-rich dialogue systems. An open-source library DeepPavlov …
General Classificationintent-classificationIntent Classificationnamed-entity-recognition+3Multi-Layer Ensembling Techniques for Multilingual Intent Classification
In this paper we determine how multi-layer ensembling improves performance on multilingual intent classification. We develop a novel multi-layer ensembling approach that ensembles both different model initializations and…
ClassificationGeneral Classificationintent-classificationIntent ClassificationData Collection for Dialogue System: A Startup Perspective
Industrial dialogue systems such as Apple Siri and Google Now rely on large scale diverse and robust training data to enable their sophisticated conversation capability. Crowdsourcing provides a scalable and inexpensive …
General Classificationintent-classificationIntent ClassificationText ClassificationPractical Application of Domain Dependent Confidence Measurement for Spoken Language Understanding Systems
Spoken Language Understanding (SLU), which extracts semantic information from speech, is not flawless, specially in practical applications. The reliability of the output of an SLU system can be evaluated using a semantic…
Automatic Speech Recognition (ASR)Feature Engineeringintent-classificationIntent Classification+5