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Artificial intelligence

  1. Overview
  2. Research areas
  3. Projects
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Delivering trusted knowledge with AI

Artificial Intelligence plays a critical role at Thomson Reuters. It is embedded in how we create, enhance, connect, and deliver trusted information to our customers. It powers the products used by professionals around the world.

Since the early 1990s, we have been injecting AI and machine learning into our value creation and delivery stack. The result is comprehensive, accurate, and trusted knowledge and insights that are at the core of how professionals get their jobs done.

This is the story of AI @ TR, spanning our long history of contributions in this field of research, our current research projects, and the potential AI-enabled future of knowledge work.

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Our AI principles 

At Thomson Reuters, trust is one of our most important values. Thomson Reuters has drafted the following AI principles to promote trustworthiness in our continuous design, development, and deployment of AI. 

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Research areas

Our core set of applied research

Natural language processing

Natural Language Processing (NLP) focuses on designing algorithms to parse, analyze, mine and ultimately ‘understand’ and generate human language. NLP is one of our key-enabling technologies because we operate in text heavy industries.

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Information retrieval

Information Retrieval (IR) is concerned with helping researchers find what they are looking for. It covers all three modalities of the findability problem: search, recommender systems and navigation-based discovery.

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Machine learning

Machine Learning (ML) is the discipline of developing programs that learn from data. From classification, to mining, to predicting, ML is at the center of what we do. It is how we solve problems; it is our toolbox.

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Publications

At Thomson Reuters, we place high value on being active members of the research community. We benefit from published research in our work, so we try to contribute back by sharing some of our research and findings through publications. 

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Research projects

Document analysis 

Document analysis

Professional knowledge work is often document-centric. This research project focuses on developing algorithms and tools to automate or machine-assist document review and analysis tasks.

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Machine reading comprehension

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Machine reading comprehension (MRC) is a subfield of NLP with the long term objective of endowing machines with the capability to read, understand, reason, and answer questions about unstructured natural language text.

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Text mining

Text mining focuses on developing algorithms to extract valuable information from text to optimize knowledge tasks focusing on content organization, consumption, distribution and analysis.

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Meet our A.I. experts
Our talented team of scientists, engineers, designers and developers come from diverse backgrounds, are creative problem solvers and dedicated to advancing knowledge work with AI/ML.
A.I. @ Thomson Reuters timeline

Follow our AI @ TR timeline to discover our innovation journey - a journey that has helped us become "the answer company".

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Build a career without boundaries. Do work that matters, with the flexibility to pursue your passion wherever it leads. Bring your ambition to make a difference. We’ll bring a world of opportunities.

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