7. A non-transitory computer-readable medium having encoded therein programming code executable by a processor to perform or control performance of operations comprising: identifying, by the processor, an original topic representation for a set of electronic documents stored at least temporarily in a non-transitory storage media; performing, by the processor, an informativeness analysis on the original topic representation; performing, by the processor, a topic consistency analysis on the original topic representation, wherein performing the topic consistency analysis on the original topic representation comprises: identifying a set of knowledge points in the original topic representation; identifying a semantic vector representation of each knowledge point of the set of knowledge points; calculating a centroid of the original topic representation; calculating an average semantic distance to the centroid for the original topic representation; in response to determining that the average semantic distance to the centroid for the original topic representation is above a second threshold, removing the original topic representation; and in response to determining that the average semantic distance to the centroid for the original topic representation is below the second threshold, keeping the original topic representation; performing, by the processor, a topic redundancy analysis on the original topic representation in view of a second topic representation; and generating, by the processor, a refined topic representation based on the informativeness analysis, the consistency analysis, and the redundancy analysis.
11. The non-transitory computer-readable medium of claim 7 , wherein performing a topic redundancy analysis on the original topic representation in view of a second topic representation comprises: identifying a first set of knowledge points in the original topic representation and a second set of knowledge points in the second topic representation; identifying a semantic vector representation of each knowledge point of the first set of knowledge points and second set of knowledge points; calculating a first centroid of the original topic representation and a second centroid of the second topic representation; calculating an average semantic distance between the first centroid and the second centroid; in response to determining that the average semantic distance between the first centroid and the second centroid is below a third threshold, merging the original topic representation and the second topic representation; and in response to determining that the average semantic distance between the first centroid and the second centroid is above the third threshold, keeping the original topic representation and the second topic representation.