A Big Data-Driven Approach to Analyze the Influencing Factors of Enterprise’s Technological Innovation

Table 1

The main parameters in equations’ definitions.

Elements	Definition
tn	Text keywords
cm	Concepts in the domain ontology
	Unregistered word
TF	The frequency of the keyword in dataset
μ	The threshold value of keyword frequency
M	The semantic similarity and the relatedness matrix
dist(ci, cj)	The semantic distance between concepts ci and cj in ontology
λ	The influence factor of semantic distance on semantic similarity
f^k(ci, cj)	The number of times that concept ci and cj appear simultaneously in the k words window at the entire corpus
f^c(ci)	The frequency of the concept ci at the entire corpus
rel(ci, cj)	Relatedness between concept ci and cj
Sim_Rel(ci, cj)	Semantic similarity and relatedness between concept of ci and cj
α	The adjusting parameter
di	The text document
	The weight of the term tj in the document di
tj	The feature vector of the document
zl	The cluster centre
	The new document feature vector derived from tj
	The cluster centre derived from zl