Papers Entity Resolution
“Entity Resolution” 태그가 달린 논문 214편 · 필터 해제
Local Embeddings for Relational Data Integration
Deep learning based techniques have been recently used with promising results for data integration problems. Some methods directly use pre-trained embeddings that were trained on a large corpus such as Wikipedia. However…
Data IntegrationEntity ResolutionSentenceZeroER: Entity Resolution using Zero Labeled Examples
Entity resolution (ER) refers to the problem of matching records in one or more relations that refer to the same real-world entity. While supervised machine learning (ML) approaches achieve the state-of-the-art results, …
Entity ResolutionThe Swedish PoliGraph: A Semantic Graph for Argument Mining of Swedish Parliamentary Data
As part of a larger project on argument mining of Swedish parliamentary data, we have created a semantic graph that, together with named entity recognition and resolution (NER), should make it easier to establish connect…
Argument MiningEntity Resolutionnamed-entity-recognitionNamed Entity Recognition+2Optimal Transport-based Alignment of Learned Character Representations for String Similarity
String similarity models are vital for record linkage, entity resolution, and search. In this work, we present STANCE --a learned model for computing the similarity of two strings. Our approach encodes the characters of …
Entity ResolutionCrowdsourcing and Aggregating Nested Markable Annotations
One of the key steps in language resource creation is the identification of the text segments to be annotated, or markables, which depending on the task may vary from nominal chunks for named entity resolution to (potent…
coreference-resolutionCoreference ResolutionEntity ResolutionText SegmentationLow-resource Deep Entity Resolution with Transfer and Active Learning
Entity resolution (ER) is the task of identifying different representations of the same real-world entities across databases. It is a key step for knowledge base creation and text mining. Recent adaptation of deep learni…
Active LearningEntity ResolutionFeature EngineeringTransfer LearningKnowledge Refinement via Rule Selection
In several different applications, including data transformation and entity resolution, rules are used to capture aspects of knowledge about the application at hand. Often, a large set of such rules is generated automati…
Entity ResolutionTopological and Semantic Graph-based Author Disambiguation on DBLP Data in Neo4j
In this work, we introduce a novel method for entity resolution author disambiguation in bibliographic networks. Such a method is based on a 2-steps network traversal using topological similarity measures for rating cand…
Entity ResolutionLink PredictionSpecificityNSEEN: Neural Semantic Embedding for Entity Normalization
Much of human knowledge is encoded in text, available in scientific publications, books, and the web. Given the rapid growth of these resources, we need automated methods to extract such knowledge into machine-processabl…
Entity ResolutionKnowledge GraphsIntegrating User Feedback under Identity Uncertainty in Knowledge Base Construction
Users have tremendous potential to aid in the construction and maintenance of knowledges bases (KBs) through the contribution of feedback that identifies incorrect and missing entity attributes and relations. However, as…
Entity ResolutionKnowledge Base ConstructionGradual Machine Learning for Entity Resolution
Usually considered as a classification problem, entity resolution (ER) can be very challenging on real data due to the prevalence of dirty values. The state-of-the-art solutions for ER were built on a variety of learning…
BIG-bench Machine LearningEntity ResolutionGeneral ClassificationProbabilistic Blocking with An Application to the Syrian Conflict
Entity resolution seeks to merge databases as to remove duplicate entries where unique identifiers are typically unknown. We review modern blocking approaches for entity resolution, focusing on those based upon locality …
BlockingEntity ResolutionInformation RetrievalRetrievalA Practical Approach to Proper Inference with Linked Data
Entity resolution (ER), comprising record linkage and de-duplication, is the process of merging noisy databases in the absence of unique identifiers to remove duplicate entities. One major challenge of analysis with link…
Entity ResolutionLearning Text Representations for 500K Classification Tasks on Named Entity Disambiguation
Named Entity Disambiguation algorithms typically learn a single model for all target entities. In this paper we present a word expert model and train separate deep learning models for each target entity string, yielding …
AllData AugmentationEntity DisambiguationEntity Linking+4Scalable Matching and Clustering of Entities with FAMER
Entity resolution identifies semantically equivalent entities, e.g. describing the same product or customer. It is especially challenging for Big Data applications where large volumes of data from many sources have to be…
ClusteringClustering Algorithms EvaluationEntity ResolutionReuse and Adaptation for Entity Resolution through Transfer Learning
Entity resolution (ER) is one of the fundamental problems in data integration, where machine learning (ML) based classifiers often provide the state-of-the-art results. Considerable human effort goes into feature enginee…
Data IntegrationEntity ResolutionFeature EngineeringTransfer LearningExploiting Structure in Representation of Named Entities using Active Learning
Fundamental to several knowledge-centric applications is the need to identify named entities from their textual mentions. However, entities lack a unique representation and their mentions can differ greatly. These variat…
Active LearningEntity LinkingEntity ResolutionQuestion Answering+2Automatic Curation and Visualization of Crime Related Information from Incrementally Crawled Multi-source News Reports
In this paper, we demonstrate a system for the automatic extraction and curation of crime-related information from multi-source digitally published News articles collected over a period of five years. We have leveraged t…
ArticlesEntity ResolutionGeneral Context-Aware Data Matching and Merging Framework
Due to numerous public information sources and services, many methods to combine heterogeneous data were proposed recently. However, general end-to-end solutions are still rare, especially systems taking into account dif…
AttributeEntity ResolutionManagementEntity Resolution and Location Disambiguation in the Ancient Hindu Temples Domain using Web Data
We present a system for resolving entities and disambiguating locations based on publicly available web data in the domain of ancient Hindu Temples. Scarce, unstructured information poses a challenge to Entity Resolution…
ClusteringEntity Resolution