Web of Science Research Assistant
A generative-AI-powered tool that helps you quickly find the right content and easily navigate complex research tasks
Enhance your research with a responsibly developed, generative AI-powered tool.
Discover fresh insights faster so you can focus on creating new knowledge. Far more than a chatbot, the Web of Science™ Research Assistant runs alongside you as you work, keeping up with your research needs as they develop. Wherever you are in your career, start getting more out of the world’s most trusted citation database—the Web of Science Core Collection™.
Leverage time-saving technologies with confidence
Implement responsible AI tools
High-quality content
Powered by carefully curated data from editorially selected sources—Web of Science Core Collection data—to ensure that the tool delivers insights that add value to your research process.
Community engagement
Developed in partnership with researchers and librarians to ensure that the tool solves the most pertinent problems in ways that deliver trust in the technology and its application.
Responsible application
Designed to help you understand how content is generated and interrogate responses. Aligned with evolving licensing and usage rights in the AI landscape.
Streamline literature review with agentic AI
Introducing an enhanced literature review guide in Web of Science Research Assistant
Optimize your query, identify research gaps and hotspots and formulate hypotheses with the help of the new literature review guide in Web of Science Research Assistant. Powered by responsible Academic AI and trusted Web of Science Core Collection data, the advanced AI agent enables you to synthesize the literature more efficiently.
Cut through the complexity of publication and citation data
Grasp core concepts faster
Conduct natural language searches in several languages and receive concise overviews and commentaries that consider over 120 years of research.
Determine your next research step
Navigate research tasks with guided walkthroughs and save time with context-specific prompts delivered as you work. Identify experts to develop your collaboration strategy.
Uncover meaningful connections
Explore dynamic visualizations and carry out light analytics quickly with the help of co-citation networks, topic maps, trend graphs and more.
Resources
Frequently asked questions
When you submit a question to the assistant, it starts by retrieving articles that exhibit the highest degree of semantic similarity to your query and then complements those with additional highly relevant results based on keywords. From there, it ranks results based on a similarity score and runs them through a proprietary algorithm to ensure that the most valuable and pertinent resources are highlighted. Top publications are then chosen to formulate a response to your query. Additional layers of relevancy ranking reduce noise in your results sets.
We use commercially provided pre-trained Large Language Models in a Retrieval Augmented Generation architecture (RAG). We do not train our own models. While we are using the pre-trained LLMs to support the creation of narrative content, the facts in this content are generated from our trusted academic sources. We test this setup rigorously to ensure academic integrity and alignment with the academic ecosystem. Testing includes validation of responses through academic subject matter experts who evaluate the outputs for accuracy and relevance. Additionally, we conduct extensive user testing that involve real-world research and learning scenarios to further refine accuracy and performance.
We are committed to the highest standards of user privacy and security. We do not share or pass any publisher content, library-owned materials, or user data to large language models (LLMs) for any purpose.
Data privacy and trust are top priorities when designing our AI tools. We comply with data privacy regulations and adhere to the evolving global AI legislation.
As part of the user query, only the content that users themselves input into the query is transmitted to the LLM. No additional data is shared during this process, ensuring the protection of sensitive information. Furthermore, we are not using any of the LLM API endpoints directly but accessing LLMs through a private setup. This ensures that data entered by users in the query stays protected and cannot be seen or accessed by any other party. This approach to data protection aligns with our practices in academic search, where we apply our knowledge in securely managing user information. For more information on our privacy and data protection program, visit: https://clarivate.com/privacy-center/
We have developed the Clarivate Academic AI Platform that is designed to help us bring existing and new solutions to the market faster and support multiple use cases at scale. The platform will allow us to deliver more capabilities, such as semantic search and more, with a consistent user experience, in a safe and secure environment that ensures user privacy and data security. The platform will serve all Clarivate academic solutions.
The AI Platform is not just about infrastructure. The AI Platform team serves as an AI center of excellence with strong LLM stewardship, supporting the different product teams in using AI responsibly, and providing strong governance to make sure that AI is applied responsibly. The team also works closely with the community. They have built an AI Advisory council, with the goal of sharing insights & findings, evaluating results, gathering feedback from librarians, students, and faculty, mitigating inaccuracies & bias issues, and sharing adoption best practices.
Ensuring clarity and trust in our solutions is one of our top priorities. Our conversational discovery and AI-powered tools present a list of academic resources on which their responses are based, so that you can always explore relevant materials for further context.
