1. A method of modifying semantic similarity graphs representative of pair-wise similarity between documents in a corpus, the method comprising: obtaining, with one or more processors, a semantic similarity graph that comprises more than 500 nodes and more than 1000 weighted edges, each node representing a document of a corpus, and each edge weight indicating an amount of similarity between a pair of documents corresponding to the respective nodes connected by the respective edge; after obtaining the semantic similarity graph, obtaining, with one or more processors, a n-gram indicating a request that edge weights affected by the n-gram are to be increased or decreased; expanding, with one or more processors, the n-gram to produce a set of expansion n-grams, wherein expanding the n-gram comprises: determining which documents in at least part of the corpus contain the n-gram to form a first set of documents; determining which documents in at least part of the corpus do not contain the n-gram to form a second set of documents, the first set of documents and the second set of documents each including more than 20 documents; selecting a set of candidate n-grams from the first set of documents, the set of candidate n-grams having more than five n-grams; determining an amount of times each candidate n-gram occurs in the first set of documents to form a first amount; determining an amount of times each candidate n-gram occurs in the second set of documents to form a second amount; determining, for each of the candidate n-grams, a candidate n-gram score based on the first amount and the second amount, wherein the candidate n-gram scores tends to increase or decrease as a ratio of the first amount to the second amount increases or decreases; and selecting expansion n-grams based on the candidate n-gram scores, the expansion n-grams and n-gram collectively forming an adjustment n-gram set; adjusting, with one or more processors, edge weights of the semantic similarity graph of edges between pairs of documents in which members of the adjustment n-gram set co-occur in response to determining that the respective documents contain a member of the adjustment n-gram set, wherein the expansion n-grams are inferred to be conceptually related to the obtained n-gram indicating the request, and wherein the expansion n-grams cause the adjustment of edge weights to be a more comprehensive response to the request than an adjustment based solely on the obtained n-gram indicating the request; and storing the adjusted weights in memory.
17. The method of claim 1 , wherein the n-gram is obtained based on a cluster of the semantic similarity graph selected by a user.