1. A method for approximate named-entity extraction from a dictionary comprising a plurality of entries, each of the entries including one or more words, the method comprising: reading a plurality of the words from the entries of the dictionary; searching network resources to determine a frequency of occurrence of the words on the network resources; in view of the frequency of occurrence of the words located on the network resources, determining domain relevancy of the words in the entries of the dictionary; creating a domain repository using top-ranked words as determined by the domain relevancy of the words; in view of the domain repository, computing signatures for both the entries of the dictionary and strings of an input document as representative strings that capture domain-related information based on a domain knowledge base; filtering the strings of the input document by comparing the signatures of the strings against the signatures of the entries to identify approximate-match entity names, the filtering further comprising: storing the signatures for the entries in a signature Bloom filter, wherein comparing the signatures of the strings is performed against the signatures of the entries in the signature Bloom filter; creating a length-based inverted index as a list of unique tokens from the dictionary indicating the entries where the tokens occur, the signatures of the entries, and a number of tokens per entry; and narrowing a search range when filtering the strings using the length-based inverted index to identify approximate matches having matching signatures and a similar length in view of the number of tokens per entry compared to a number of tokens per string of the input document as bounded by a parameter that establishes the search range relative to the number of tokens per string of the input document; and generating a list of the approximate-match entity names as identified based on the filtering.