An overview of end-to-end entity resolution for big data
One of the most critical tasks for improving data quality and increasing the reliability of data
analytics is Entity Resolution (ER), which aims to identify different descriptions that refer to …
analytics is Entity Resolution (ER), which aims to identify different descriptions that refer to …
Knowledge graphs: A practical review of the research landscape
M Kejriwal - Information, 2022 - mdpi.com
Knowledge graphs (KGs) have rapidly emerged as an important area in AI over the last ten
years. Building on a storied tradition of graphs in the AI community, a KG may be simply …
years. Building on a storied tradition of graphs in the AI community, a KG may be simply …
[ΒΙΒΛΙΟ][B] Domain-specific knowledge graph construction
M Kejriwal - 2019 - Springer
Domain-specific knowledge graphs have emerged as a field unto their own, steadily and
perhaps not so slowly. Graphs have been pervasive in AI for a long period of time, dating …
perhaps not so slowly. Graphs have been pervasive in AI for a long period of time, dating …
Machine Learning for Refining Knowledge Graphs: A Survey
Knowledge graph (KG) refinement refers to the process of filling in missing information,
removing redundancies, and resolving inconsistencies in KGs. With the growing popularity …
removing redundancies, and resolving inconsistencies in KGs. With the growing popularity …
End-to-end entity resolution for big data: A survey
One of the most important tasks for improving data quality and the reliability of data analytics
results is Entity Resolution (ER). ER aims to identify different descriptions that refer to the …
results is Entity Resolution (ER). ER aims to identify different descriptions that refer to the …
Unsupervised entity resolution on multi-type graphs
Entity resolution is the task of identifying all mentions that represent the same real-world
entity within a knowledge base or across multiple knowledge bases. We address the …
entity within a knowledge base or across multiple knowledge bases. We address the …
[PDF][PDF] Knowledge graphs and COVID-19: opportunities, challenges, and implementation
M Kejriwal - Harv. Data Sci. Rev, 2020 - assets.pubpub.org
The COVID-19 pandemic has been truly global and multidimensional in scope, with
ramifications extending well beyond health. Yet, unlike previous crises, there is hope that …
ramifications extending well beyond health. Yet, unlike previous crises, there is hope that …
Detection of malicious Android applications using Ontology-based intelligent model in mobile cloud environment
JN OS - Journal of Information Security and Applications, 2021 - Elsevier
Abstract Mobile Cloud Computing (MCC) is a computing model that makes mobile devices
resourceful by executing mobile applications (apps) in the cloud and storing data in cloud …
resourceful by executing mobile applications (apps) in the cloud and storing data in cloud …
Named entity resolution in personal knowledge graphs
M Kejriwal - arxiv preprint arxiv:2307.12173, 2023 - arxiv.org
Entity Resolution (ER) is the problem of determining when two entities refer to the same
underlying entity. The problem has been studied for over 50 years, and most recently, has …
underlying entity. The problem has been studied for over 50 years, and most recently, has …
A review of unsupervised and semi-supervised blocking methods for record linkage
K O'Hare, A Jurek-Loughrey, C Campos - Linking and Mining …, 2019 - Springer
Record linkage, referred to also as entity resolution, is a process of identifying records
representing the same real-world entity (eg a person) across varied data sources. To reduce …
representing the same real-world entity (eg a person) across varied data sources. To reduce …