Knowledge model: a method to evaluate an individual's knowledge quantitatively
This addresses the need for accurate knowledge assessment in fields like research and education, though it appears incremental as it builds on existing topic modeling techniques.
The paper tackles the problem of quantitatively evaluating a knowledge worker's knowledge without exams by proposing a knowledge model that analyzes learning experiences using topic models to calculate scores for knowledge points, and it develops a preliminary system to test its practicability.
As the quantity of human knowledge increasing rapidly, it is harder and harder to evaluate a knowledge worker's knowledge quantitatively. There are lots of demands for evaluating a knowledge worker's knowledge. For example, accurately finding out a researcher's research concentrations for the last three years; searching for common topics for two scientists with different academic backgrounds; helping a researcher discover his deficiencies on a research field etc. This paper proposes a method named knowledge model to evaluate a knowledge worker's knowledge quantitatively without taking an examination. It records and analyzes an individual's each learning experience, discovering all the involved knowledge points and calculating their shares by analyzing the text learning contents with topic model. It calculates a score for a knowledge point by accumulating the effects of one's all learning experiences about it. A preliminary knowledge evaluating system is developed to testify the practicability of knowledge model.