| 摘要 |
A system for analyzing text-based information is presented. Each datum of information includes an author, a description and a timestamp. A fetcher fetches the raw information according to keywords. A parser parses the raw information to refine the results. A lexicon management module extracts lemmas from the raw information, and creates an edited lexicon containing the raw data and the lemmas for each datum. A data manager correlates lemmas in the edited lexicon and identifies clusters of lemmas that are correlated between each other. The results can be visually displayed to a user, and clusters of lemma that are less correlated than the other clusters can be visually identified. In one aspect, the user is able to excise the less correlated clusters, in order to further refine the results of the keyword search.
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