Papers Entity Resolution
“Entity Resolution” 태그가 달린 논문 214편 · 필터 해제
Profiling Entity Matching Benchmark Tasks
Entity matching is a central task in data integration which has been researched for decades. Over this time, a wide range of benchmark tasks for evaluating entity matching methods has been developed. This resource paper …
Data IntegrationEntity ResolutionFeature EngineeringAutomated Metadata Harmonization Using Entity Resolution & Contextual Embedding
ML Data Curation process typically consist of heterogeneous & federated source systems with varied schema structures; requiring curation process to standardize metadata from different schemas to an inter-operable schema.…
Entity ResolutionA Deep Learning Approach to Geographical Candidate Selection through Toponym Matching
Recognizing toponyms and resolving them to their real-world referents is required for providing advanced semantic access to textual data. This process is often hindered by the high degree of variation in toponyms. Candid…
Deep LearningEntity ResolutionOptical Character Recognition (OCR)Toponym ResolutionCorDEL: A Contrastive Deep Learning Approach for Entity Linkage
Entity linkage (EL) is a critical problem in data cleaning and integration. In the past several decades, EL has typically been done by rule-based systems or traditional machine learning models with hand-curated features,…
Deep LearningEntity ResolutionSimulating Name-like Vectors for Testing Large-scale Entity Resolution
Accurate and efficient entity resolution (ER) has been a problem in data analysis and data mining projects for decades. In our work, we are interested in developing ER methods to handle big data. Good public datasets are…
Entity ResolutionIntermediate Training of BERT for Product Matching
Transformer-based models like BERT have pushed the state-of the-art for a wide range of tasks in natural language processing. General-purpose pre-training on large corpora allows Transformers to yield good performance ev…
Entity ResolutionLanguage ModelingLanguage ModellingMasked Language Modeling(Almost) All of Entity Resolution
Whether the goal is to estimate the number of people that live in a congressional district, to estimate the number of individuals that have died in an armed conflict, or to disambiguate individual authors using bibliogra…
AllClusteringEntity ResolutionA Study on Entity Resolution for Email Conversations
This paper investigates the problem of entity resolution for email conversations and presents a seed annotated corpus of email threads labeled with entity coreference chains. Characteristics of email threads concerning r…
Entity ResolutionAuthor Name Disambiguation in Bibliographic Databases: A Survey
Entity resolution is a challenging and hot research area in the field of Information Systems since last decade. Author Name Disambiguation (AND) in Bibliographic Databases (BD) like DBLP , Citeseer , and Scopus is a spec…
ClusteringEntity ResolutionSurveyDeep Entity Matching with Pre-Trained Language Models
We present Ditto, a novel entity matching system based on pre-trained Transformer-based language models. We fine-tune and cast EM as a sequence-pair classification problem to leverage such models with a simple architectu…
Data AugmentationEntity ResolutionClustering with Fast, Automated and Reproducible assessment applied to longitudinal neural tracking
Across many areas, from neural tracking to database entity resolution, manual assessment of clusters by human experts presents a bottleneck in rapid development of scalable and specialized clustering methods. To solve th…
ClusteringEntity ResolutionModel SelectionSpike SortingThe STEM-ECR Dataset: Grounding Scientific Entity References in STEM Scholarly Content to Authoritative Encyclopedic and Lexicographic Sources
We introduce the STEM (Science, Technology, Engineering, and Medicine) Dataset for Scientific Entity Extraction, Classification, and Resolution, version 1.0 (STEM-ECR v1.0). The STEM-ECR v1.0 dataset has been developed t…
Entity Extraction using GANEntity LinkingEntity ResolutionGeneral Classification+1Crowdsourced Collective Entity Resolution with Relational Match Propagation
Knowledge bases (KBs) store rich yet heterogeneous entities and facts. Entity resolution (ER) aims to identify entities in KBs which refer to the same real-world object. Recent studies have shown significant benefits of …
AttributeEntity ResolutionQuestion SelectionPre-Training for Query Rewriting in A Spoken Language Understanding System
Query rewriting (QR) is an increasingly important technique to reduce customer friction caused by errors in a spoken language understanding pipeline, where the errors originate from various sources such as speech recogni…
Entity ResolutionFrictionLanguage ModelingLanguage Modelling+4AutoBlock: A Hands-off Blocking Framework for Entity Matching
Entity matching seeks to identify data records over one or multiple data sources that refer to the same real-world entity. Virtually every entity matching task on large datasets requires blocking, a step that reduces the…
BlockingEntity ResolutionRepresentation LearningTowards Interpretable and Learnable Risk Analysis for Entity Resolution
Machine-learning-based entity resolution has been widely studied. However, some entity pairs may be mislabeled by machine learning models and existing studies do not study the risk analysis problem -- predicting and inte…
BIG-bench Machine LearningEntity ResolutionEntity resolution for noisy ASR transcripts
Large vocabulary domain-agnostic Automatic Speech Recognition (ASR) systems often mistranscribe domain-specific words and phrases. Since these generic ASR systems are the first component of most voice assistants in produ…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Entity ResolutionInformation Retrieval+4d-blink: Distributed End-to-End Bayesian Entity Resolution
Entity resolution (ER; also known as record linkage or de-duplication) is the process of merging noisy databases, often in the absence of unique identifiers. A major advancement in ER methodology has been the application…
BlockingEntity ResolutionAccelerating Column Generation via Flexible Dual Optimal Inequalities with Application to Entity Resolution
In this paper, we introduce a new optimization approach to Entity Resolution. Traditional approaches tackle entity resolution with hierarchical clustering, which does not benefit from a formal optimization formulation. I…
ClusteringEntity ResolutionLearning to Sample: an Active Learning Framework
Meta-learning algorithms for active learning are emerging as a promising paradigm for learning the ``best'' active learning strategy. However, current learning-based active learning approaches still require sufficient tr…
Active LearningDiversityEntity Resolutionimage-classification+2