1. A computer implemented method comprising: accessing a digital document, wherein the digital document relates to one or more topics; generating a list of expert students, wherein the expert students have authored one or more annotations relating to a topic similar to the one or more topics in the digital document by: extracting similar documents from a database of digital documents; filtering the similar documents into a set of documents that one or more users have annotated; computing a confidence score for each annotation imported by a user; and computing a local user rank of each expert student based on the confidence score; ordering the list of expert students according to the local user rank, wherein the local user rank identifies a level of expertise of the expert students; and presenting the ordered list of expert students, where the ordered list comprises a pre-defined number of expert students with a level of expertise meeting a predefined threshold.
5. The method of claim 1 , further comprising: extracting one or more keywords of the digital document; determining the similar documents based on presence of the keywords in the similar documents, wherein the similar documents also comprise one or more digital documents; extracting pages of relevant documents from the similar documents, the relevant documents being those documents annotated by one or more of the expert students, wherein context of the extracted pages is similar to context of a page in the digital document; and ordering the list of expert students by also taking into account a measure of a similarity of the extracted pages when computing the local user rank.