  In the era of big data, intellectual property-oriented scientific and
technological resources show the trend of large data scale, high information
density and low value density, which brings severe challenges to the effective
use of intellectual property resources, and the demand for mining hidden
information in intellectual property is increasing. This makes intellectual
property-oriented science and technology resource portraits and analysis of
evolution become the current research hotspot. This paper sorts out the
construction method of intellectual property resource intellectual portrait and
its pre-work property entity extraction and entity completion from the aspects
of algorithm classification and general process, and directions for improvement
of future methods.
