with sampling to efficiently identify and cleanse a database. The experimental evaluation shows that for proper nouns the center calculation and border detection algorithms are robust and even very small sample sizes yield good results. 1

vagueness of queries and uncertainty of knowledge. In this paper, we focus on searching proper nouns. Here the vagueness stems from limited knowledge a user has about his information need. If he is e.g. searching for papers of a certain author in a bibliographic database, he will not be successful if he

on names and ad-dresses, since they can complement orthographic search algorithms that make use of permutation, deletion, and insertion by allowing for a comparison with the phonetic equivalent. In databases, phonetics can help retrieve a word or a proper name without the user needing to know the correct

application that analysis possible misspelling in a text by referring to the accepted spellings in a database. In the database various accurate words of the target language for which the spell -checker is to be made are stored which consists of proper nouns for males, females, countries, states, rivers

den angegebenen Quellen und Hilfsmitteln angefertigt zu haben. Alle Stellen, die aus Quellen entnommen wurden, sind als solche kenntlich gemacht. Diese Arbeit hat in gleicher oder ähnlicher Form noch keiner Prüfungsbehörde vorgelegen. Darmstadt, den 26.06.2012 (T. Kilian) Contents

by such vertical links, we remove any mentions of customers and suppliers using 81 phrases listed in the Internet Appendix. 23 Ultimately, we represent both firm vocabularies and the commodity vocabularies from BEA as vectors with length 60,507, which is the number of nouns and proper nouns appearing in 10-K