Wikipedia articles contain, besides free text, various types of structured information in the form of wiki markup. The type of wiki content that is most valuable for search are Wikipedia infoboxes, which display an article’s most relevant facts as a table of attribute-value pairs on the top right-hand side of the Wikipedia page. Infobox data is not used by Wikipedia’s own search engine. Standar...

In this paper, we discuss how text mining methods could be used for intelligence analysis. We describe how simple methods from text mining can be used to help intelligence analysts determine where a specific report or analysis fits into the knowledge base (KB), i.e., how it should be classified and which, if any, other documents in the KB it should be linked to. The method works by comparing th...

As one of the fundamental tasks in text analysis, phrase mining aims at extracting quality phrases from a text corpus. Phrase mining is important in various tasks including automatic term recognition, document indexing, keyphrase extraction, and topic modeling. Most existing methods rely on complex, trained linguistic analyzers, and thus likely have unsatisfactory performance on text corpora of...

Wikipedia provides a knowledge base for computing word relatedness in a more structured fashion than a search engine and with more coverage than WordNet. In this work we present experiments on using Wikipedia for computing semantic relatedness and compare it to WordNet on various benchmarking datasets. Existing relatedness measures perform better using Wikipedia than a baseline given by Google ...

In this paper, we discuss how text mining methods could be used in a mixedinitiative interaction approach to intelligence analysis. We describe how simple methods from text mining can be used to help intelligence analysts determine where a specific report or analysis fits into the knowledge base (KB), i.e., how it should be classified and which, if any, other documents in the KB it should be li...