Postcorrection of OCR-results for text documents is usually based on electronic dictionaries. When scanning texts from a specific thematic area, conventional dictionaries often miss a considerable number of tokens. Furthermore, if word frequencies are stored with the entries, these frequencies will not properly reflect the frequencies found in the given thematic area. Correction adequacy suffer...

1. Background With the development of digital technology, types of learners’ dictionaries have been diversified during the last two decades. Digitized dictionaries such as those on CD-ROM and the Web have become widespread (e.g., Aust, Kelley, & Roby, 1993). Particularly, with the advent of hand-held electronic dictionaries (henceforth ED), the number of ED users has been rapidly expanding in J...

Polarity classification of words is important for applications such as Opinion Mining and Sentiment Analysis. A number of sentiment word/sense dictionaries have been manually or (semi)automatically constructed. The dictionaries have substantial inaccuracies. Besides obvious instances, where the same word appears with different polarities in different dictionaries, the dictionaries exhibit compl...

Automatic acquisition of raw source material is of great aid for the compilation of dictionaries, and, in particular, of specialized dictionaries such as collocation dictionaries. The extraction of collocations from corpora has been actively worked on since the late eighties. The quality of the state-of-the-art extraction algorithms allows the lexicographers to obtain lists of collocations they...

This study looks at how well the leading monolingual English learners’ dictionaries in their online versions cope with misspelled words as search terms. Six such dictionaries are tested on a corpus of misspellings produced by Polish, Japanese, and Finnish learners of English. The performance of the dictionaries varies widely, but is in general poor. For a large proportion of cases, dictionaries...