Papers Entity Resolution
“Entity Resolution” 태그가 달린 논문 214편 · 필터 해제
Concept Identification of Directly and Indirectly Related Mentions Referring to Groups of Persons
Unsupervised concept identification through clustering, i.e., identification of semantically related words and phrases, is a common approach to identify contextual primitives employed in various use cases, e.g., text dim…
ArticlesClusteringDimensionality ReductionEntity ResolutionTowards a Query-Optimal and Time-Efficient Algorithm for Clustering with a Faulty Oracle
Motivated by applications in crowdsourced entity resolution in database, signed edge prediction in social networks and correlation clustering, Mazumdar and Saha [NIPS 2017] proposed an elegant theoretical model for study…
ClusteringEntity ResolutionOpen-Ended Question AnsweringStochastic Block ModelOptimizing NLU Reranking Using Entity Resolution Signals in Multi-domain Dialog Systems
In dialog systems, the Natural Language Understanding (NLU) component typically makes the interpretation decision (including domain, intent and slots) for an utterance before the mentioned entities are resolved. This may…
Entity Resolutionintent-classificationIntent ClassificationNatural Language Understanding+1Entity Resolution in Open-domain Conversations
In recent years, incorporating external knowledge for response generation in open-domain conversation systems has attracted great interest. To improve the relevancy of retrieved knowledge, we propose a neural entity link…
Entity LinkingEntity Resolutionnamed-entity-recognitionNamed Entity Recognition+3xER: An Explainable Model for Entity Resolution using an Efficient Solution for the Clique Partitioning Problem
In this paper, we propose a global, self- explainable solution to solve a prominent NLP problem: Entity Resolution (ER). We formu- late ER as a graph partitioning problem. Every mention of a real-world entity is represen…
Entity Resolutiongraph partitioningDual-Objective Fine-Tuning of BERT for Entity Matching
An increasing number of data providers have adopted shared numbering schemes such as GTIN, ISBN, DUNS, or ORCID numbers for identifying entities in the respective domain. This means for data integration that shared ident…
Data IntegrationEntity ResolutionMulti-class ClassificationRotom: A Meta-Learned Data Augmentation Framework for Entity Matching, Data Cleaning, Text Classification, and Beyond
Deep Learning revolutionizes almost all fields of computer science including data management. However, the demand for high-quality training data is slowing down deep neural nets' wider adoption. To this end, data augment…
Data AugmentationEntity ResolutionManagementMeta-Learning+2CEREC: A Corpus for Entity Resolution in Email Conversations
We present the first large scale corpus for entity resolution in email conversations (CEREC). The corpus consists of 6001 email threads from the Enron Email Corpus containing 36,448 email messages and 60,383 entity coref…
coreference-resolutionCoreference ResolutionEntity ResolutionGraph Neural Networks for Inconsistent Cluster Detection in Incremental Entity Resolution
Online stores often utilize product relationships such as bundles and substitutes to improve their catalog quality and guide customers through myriad choices. Entity resolution using pairwise product matching models offe…
Entity ResolutionGraph Classificationgraph partitioningDeep Indexed Active Learning for Matching Heterogeneous Entity Representations
Given two large lists of records, the task in entity resolution (ER) is to find the pairs from the Cartesian product of the lists that correspond to the same real world entity. Typically, passive learning methods on such…
Active LearningBlockingEntity ResolutionLanguage ModellingPersonalized Entity Resolution with Dynamic Heterogeneous Knowledge Graph Representations
The growing popularity of Virtual Assistants poses new challenges for Entity Resolution, the task of linking mentions in text to their referent entities in a knowledge base. Specifically, in the shopping domain, customer…
Entity ResolutionRerankingGenerating automatically labeled data for author name disambiguation: An iterative clustering method
To train algorithms for supervised author name disambiguation, many studies have relied on hand-labeled truth data that are very laborious to generate. This paper shows that labeled training data can be automatically gen…
ClusteringEntity ResolutionEAGER: Embedding-Assisted Entity Resolution for Knowledge Graphs
Entity Resolution (ER) is a constitutional part for integrating different knowledge graphs in order to identify entities referring to the same real-world object. A promising approach is the use of graph embeddings for ER…
AttributeEntity ResolutionKnowledge GraphsActive Deep Learning on Entity Resolution by Risk Sampling
While the state-of-the-art performance on entity resolution (ER) has been achieved by deep learning, its effectiveness depends on large quantities of accurately labeled training data. To alleviate the data labeling burde…
Active LearningDeep LearningEntity ResolutionErGAN: Generative Adversarial Networks for Entity Resolution
Entity resolution targets at identifying records that represent the same real-world entity from one or more datasets. A major challenge in learning-based entity resolution is how to reduce the label cost for training. Du…
DiversityEntity ResolutionGenerative Adversarial NetworkAdaptive Deep Learning for Entity Resolution by Risk Analysis
The state-of-the-art performance on entity resolution (ER) has been achieved by deep learning. However, deep models are usually trained on large quantities of accurately labeled training data, and can not be easily tuned…
Deep LearningEntity ResolutionTransfer LearningRPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation
Can AI help automate human-easy but computer-hard data preparation tasks that burden data scientists, practitioners, and crowd workers? We answer this question by presenting RPT, a denoising auto-encoder for tuple-to-X m…
AllDecoderDenoisingEntity Resolution+4Graph-based Aspect Representation Learning for Entity Resolution
Entity Resolution (ER) identifies records that refer to the same real-world entity. Deep learning approaches improved the generalization ability of entity matching models, but hardly overcame the impact of noisy or incom…
Entity ResolutionLink PredictionRepresentation LearningCost-effective Variational Active Entity Resolution
Accurately identifying different representations of the same real-world entity is an integral part of data cleaning and many methods have been proposed to accomplish it. The challenges of this entity resolution task that…
Active LearningEntity ResolutionRepresentation LearningSpecificity+1Biomedical Named Entity Recognition at Scale
Named entity recognition (NER) is a widely applicable natural language processing task and building block of question answering, topic modeling, information retrieval, etc. In the medical domain, NER plays a crucial role…
De-identificationEntity ResolutionGPUInformation Retrieval+8