An Overview of Microsoft Academic Service (MAS) and Applications

Abstract

In this paper we describe a new release of a Web scale entity graph that serves as the backbone of Microsoft Academic Service (MAS), a major production effort with a broadened scope to the namesake vertical search engine that has been publicly available since 2008 as a research prototype. At the core of MAS is a heterogeneous entity graph comprised of six types of entities that model the scholarly activities: field of study, author, institution, paper, venue, and event. In addition to obtaining these entities from the publisher feeds as in the previous effort, we in this version include data mining results from the Web index and an in-house knowledge base from Bing, a major commercial search engine. As a result of the Bing integration, the new MAS graph sees significant increase in size, with fresh information streaming in automatically following their discoveries by the search engine. In addition, the rich entity relations included in the knowledge base provide additional signals to disambiguate and enrich the entities within and beyond the academic domain. The number of papers indexed by MAS, for instance, has grown from low tens of millions to 83 million while maintaining an above 95% accuracy based on test data sets derived from academic activities at Microsoft Research. Based on the data set, we demonstrate two scenarios in this work: a knowledge driven, highly interactive dialog that seamlessly combines reactive search and proactive suggestion experience, and a proactive heterogeneous entity recommendation.

Quantifying Conceptual Novelty in the Biomedical Literature

“…We use the citation information available using a collection of Web of Science PubMed citations, Microsoft Academic Graph [15] and PubMed Central. The impact of an article is measured in the following ways:

Total citation count

Journal normalized citation score , which normalizes the citations received by an article using the average citations received by all articles published in that journal in the same year.

…”

“…The methods presented here for quantifying the novelty of an article can be applied to any corpus, given that the articles are annotated with a consistent hierarchical set of categories, e.g. ACM Computing System Classification for ACM articles [2] or Microsoft Academic Graph's hierarchy of fields of study and paper keywords [15]. We complement our study with an online resource which allows a user to visually inspect the temporal profiles of all the MeSH terms assigned to a given MEDLINE article.…”

Gram

“…While the extensive graph can be presented with different views, it is not interactive, and its presentation as an "overview" makes it difficult to elicit details. The Microsoft Academic Graph is regularly updated, and is built from indexing research papers, each of which is classified into over 50,000 "fields of study" [40]. No visualization of the graph is provided, although it can be queried using different search methods, and an API is provided.…”

Leveraging Citation Networks to Visualize Scholarly Influence Over Time

“…Since the initial design study, Microsoft Academic Search has been decommissioned and replaced with Microsoft Academic, a service powered by a database called Microsoft Academic Graph (MAG), which indexes scholarly articles using content that search engine Bing crawls from the web (Sinha et al, 2015;Harzing, 2016). Since this update, Microsoft Academic has been gaining traction as a bibliometric research tool, as it approaches Google Scholar in terms of coverage while having much better structure and functionality for researchers akin to Scopus and Web of Science (Hug et al, 2017).…”