Microsoft Academic was a comprehensive research tool developed by Microsoft to assist scientists and researchers in their academic endeavors. Although the service was retired on December 31, 2021, here is an overview of what it offered during its operational period:
Purpose and Functionality
Microsoft Academic was designed to leverage machine learning and cognitive power to facilitate scientific research. It utilized AI-powered machine readers to process and analyze vast amounts of scholarly documents, extracting entities and their relationships to form a robust knowledge base known as the Microsoft Academic Graph (MAG).
Key Features
Advanced Search Capabilities
The platform provided advanced search features that allowed users to refine their queries based on various criteria such as publication date, author affiliation, journal name, and citation count. Users could also sort results by relevance or date to ensure they accessed the most up-to-date information.
Semantic Search and Recommendation
Microsoft Academic employed semantic inference to recognize query intent and retrieve the most relevant knowledge from the MAG. It acted as a personal assistant, recommending materials that users might not be aware of and alerting them to recent publications and breaking news in their field of interest.
Knowledge Acquisition and Reasoning
The service used AI to extract scholarly entities and their relationships from documents discovered by Bing crawlers. This data was organized into the MAG, which included over 150 million entities and billions of relationships, making it a scalable and comprehensive resource for academic research.
Importance Assessment and Ranking
Microsoft Academic used reinforcement learning algorithms to estimate and quantify the importance of each entity based on future citations, helping in reasoning and inferences.
Integration with Microsoft Office Suite
The platform seamlessly integrated with Microsoft Office tools such as Word and PowerPoint, allowing researchers to easily import citations, create bibliographies, and manage references. This integration streamlined the process of writing and publishing academic papers, ensuring accuracy and consistency in citation management.
Data Access and APIs
The underlying MAG data was available for download or accessible via the Academic Knowledge API. This allowed researchers and developers to use the data for various applications, including analytics, search, and recommendation scenarios. However, the API had usage limits, and users needing more extensive access could self-host the API.
Filtering and Customization
Users could filter search results by date range, author, affiliation, field of study, journal, and conference. The platform also allowed users to include or exclude news items and limit results to scholarly works only.
In summary, Microsoft Academic was a powerful tool that leveraged AI and machine learning to enhance academic research by providing advanced search capabilities, semantic recommendations, and seamless integration with other Microsoft tools. Despite its retirement, the concepts and technologies developed during its operation continue to influence the field of academic research and knowledge management.
