class_docstr: This class is used to compute graph-based IC in knowledge graph, which is
  basically the proportion of instances tagged with a specific concept
class_docstr_tok: ["This","class","is","used","to","compute","graph-based","IC","in","knowledge","graph",",","which","is","basically","the","proportion","of","instances","tagged","with","a","specific","concept"]
code: def __init__(self, ic_file):
      self._ic_file = ic_file
      self._graph_ic = self.graph_ic_reader(ic_file)
      self._graph_stats = StatSPARQL()
      self._N = self._graph_stats.entity_N()
  
imports: from abc import ABCMeta, abstractmethod
  from collections import deque
  from itertools import combinations
  import networkx
  import numpy
  from sematch.semantic.ontology import DBpedia
  from sematch.utility import FileIO
  from sematch.semantic.sparql import StatSPARQL
  import math
label_desc: Use image node_id 1 to create a new GraphIC object  with example: obj = GraphIC(ic_file)