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100 Best Relation Extraction Videos

Notes:

Relation extraction is the process of identifying and extracting relationships between entities from text or other data sources. This can be accomplished using natural language processing (NLP) techniques such as named entity recognition (NER) and dependency parsing.

Relation extraction is often used in a variety of applications, including information extraction, knowledge base construction, and text summarization. In information extraction, relation extraction can be used to identify and extract specific types of relationships between entities, such as who is married to whom, or which company a person works for. This information can then be used to populate a database or knowledge base with structured data.

In knowledge base construction, relation extraction can be used to extract relationships between entities from unstructured text and add them to a structured knowledge base. This can help to expand the scope and coverage of the knowledge base, and make it more useful for a variety of applications.

Text summarization is another application in which relation extraction can be used. By identifying and extracting relationships between entities in a text, it is possible to generate a summary of the main points or themes of the text. This can be useful for tasks such as news summarization or summarizing large volumes of text for easier consumption.

Overall, relation extraction is a powerful tool for extracting structured data from unstructured text.

See also:

100 Best GitHub: Relation Extraction | Relation Extraction & Dialog Systems | Relation Extraction & Question Answering Systems 2014 | Relation Extraction 2014 | Relation Extraction 2015


[17x Jan 2017]

  • Relation Extraction – Natural Language Processing | University of Michigan
  • Minimally Supervised Novel Relation Extraction Using a Latent Relational Mapping new
  • Text By the Bay 2015: Malcolm Greaves, Relation Extraction using Distant Supervision and SVMs
  • Core: a context-aware relation extraction method for relation completion
  • Core: a context-aware relation extraction method for relation completion
  • Congle Zhang – Exploiting Parallel News Streams for Relation Extraction
  • CoRE: A Context Aware Relation Extraction Method for Relation Completion
  • Distant Supervision for Relation Extraction using Ontology Hierarchy Based Features Demo
  • Minimally Supervised Novel Relation Extraction Using a Latent Relational Mapping
  • D2I – Miao Chen gives a talk about Semantic Relation Extraction from Socially Generated Tags
  • 10 – 4 – Semi-Supervised and Unsupervised Relation Extraction.mp4
  • 10 – 3 – Supervised Relation Extraction .mp4
  • 10 – 1 – What is Relation Extraction-.mp4
  • 10 – 4 – Semi-Supervised and Unsupervised Relation Extraction-Dan Jurafsky & Chris Manning
  • 10 – 3 – Supervised Relation Extraction – Stanford NLP – Professor Dan Jurafsky & Chris Manning
  • 10 – 1 – What is Relation Extraction- Stanford NLP – Professor Dan Jurafsky & Chris Manning
  • E-ilmu: application ACRE – Advanced Concept Relation Extraction

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