Identity Matching in News Articles with Machine Learning and NER
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Post a project like this$200
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Graphic Designer |Experienced Web Designer | Video/Audio Editor | PowerPoint/Keynote | Content Writer |
San Jose
Experienced Full Stack Web and App Developer |Android and IOS App Development| Project Management
London
214764034314163544992374646139717904899784551457280167958360598107498301102479411026184
Description
Experience Level: Entry
Use Case:
Our objective is to enhance our capability to accurately identify individuals mentioned in news articles and match them with corresponding entries in our database. Specifically, we aim to develop a machine learning model capable of discerning whether a person entity referenced in an article aligns with an individual stored within our database. This NER model will assess attributes associated with individuals in our database, and return us with a Identity Matching Scoring.
Technical Requirements:
This task involves crafting and refining a machine learning model capable of Named Entity Recognition and Linking, considering the contextual relevance of attributes associated with individuals mentioned in news articles. The model should prioritize certain attributes over others based on their relevance and significance for accurate identification and matching.
We are seeking expertise in the following areas:
Named Entity Recognition (NER) techniques
Natural Language Processing (NLP) and Machine Learning (ML) algorithms
Attribute weighting and relevance assessment
Our objective is to enhance our capability to accurately identify individuals mentioned in news articles and match them with corresponding entries in our database. Specifically, we aim to develop a machine learning model capable of discerning whether a person entity referenced in an article aligns with an individual stored within our database. This NER model will assess attributes associated with individuals in our database, and return us with a Identity Matching Scoring.
Technical Requirements:
This task involves crafting and refining a machine learning model capable of Named Entity Recognition and Linking, considering the contextual relevance of attributes associated with individuals mentioned in news articles. The model should prioritize certain attributes over others based on their relevance and significance for accurate identification and matching.
We are seeking expertise in the following areas:
Named Entity Recognition (NER) techniques
Natural Language Processing (NLP) and Machine Learning (ML) algorithms
Attribute weighting and relevance assessment
Ben T.
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27 Apr 2024
United Kingdom
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