17. A system, comprising: a topic-mining non-transitory computer-readable medium comprising instructions that, when executed by one or more processors, cause the system to: obtain a set of clauses in a first set of content items comprising unstructured data; obtain a set of stop words comprising high-frequency words that occur in a second set of content items; and automatically extract a set of topics from the set of clauses by: generating a set of n-grams from the set of clauses; excluding a first n-gram from the set of n-grams when the first n-gram contains a word in the set of stop words in a pre-specified position of the first n-gram; and applying a morphological filter to the set of n-grams to yield a subset of the set of n-grams, wherein: the set of topics comprises the subset of the set of n-grams; and the morphological filter is independent of words in the set of stop words; wherein extracting the set of topics from the set of clauses further comprises: excluding a second n-gram from the set of n-grams when the second n-gram contains a proportion of words in the set of stop words that exceeds a threshold; and a management non-transitory computer-readable medium comprising instructions that, when executed by one or more processors, cause the system to display the set of topics to a user to improve understanding of the first set of content items by the user without requiring the user to manually analyze the first set of content items.
17. A system, comprising: a topic-mining non-transitory computer-readable medium comprising instructions that, when executed by one or more processors, cause the system to: obtain a set of clauses in a first set of content items comprising unstructured data; obtain a set of stop words comprising high-frequency words that occur in a second set of content items; and automatically extract a set of topics from the set of clauses by: generating a set of n-grams from the set of clauses; excluding a first n-gram from the set of n-grams when the first n-gram contains a word in the set of stop words in a pre-specified position of the first n-gram; and applying a morphological filter to the set of n-grams to yield a subset of the set of n-grams, wherein: the set of topics comprises the subset of the set of n-grams; and the morphological filter is independent of words in the set of stop words; wherein extracting the set of topics from the set of clauses further comprises: excluding a second n-gram from the set of n-grams when the second n-gram contains a proportion of words in the set of stop words that exceeds a threshold; and a management non-transitory computer-readable medium comprising instructions that, when executed by one or more processors, cause the system to display the set of topics to a user to improve understanding of the first set of content items by the user without requiring the user to manually analyze the first set of content items. 18. The system of claim 17 , wherein obtaining the set of stop words comprising high-frequency words that occur in the second set of content items comprises: ordering a set of words in the second set of content items by frequency; and including a pre-specified number of most frequent words from the ordered set of words in the set of stop words.