  With the advent of the cloud computing era, the cost of creating, capturing
and managing information has gradually decreased. The amount of data in the
Internet is also showing explosive growth, and more and more scientific and
technological resources are uploaded to the network. Different from news and
social media data ubiquitous in the Internet, the main body of scientific and
technological resources is composed of academic-style resources or entities
such as papers, patents, authors, and research institutions. There is a rich
relationship network between resources, from which a large amount of
cutting-edge scientific and technological information can be mined. There are a
large number of management and classification standards for existing scientific
and technological resources, but these standards are difficult to completely
cover all entities and associations of scientific and technological resources,
and cannot accurately extract important information contained in scientific and
technological resources. How to construct a complete and accurate
representation of scientific and technological resources from structured and
unstructured reports and texts in the network, and how to tap the potential
value of scientific and technological resources is an urgent problem. The
solution is to construct accurate portraits of scientific and technological
resources in combination with knowledge graph related technologies.
