Techniques for automatically correcting words in text
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CIKM '93 Proceedings of the second international conference on Information and knowledge management
Implementing an efficient part-of-speech tagger
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IceTAL'10 Proceedings of the 7th international conference on Advances in natural language processing
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The information in a database is usually accessed using SQL or some other query language, but if one uses a free text retrieval system the retrieval of text based information becomes much easier and user friendly, since one can use natural languages techniques such as automatic spell checking and stemming. The free text retrieval system needs first to index the database but then it is just to search the database.Normally a search engine does not give any answers to queries when the search words does not exist in the index, therefore we connected a spell checker module into a search engine and evaluated it.The domain used was the web site of the Swedish National Tax Board (Riksskatteverket, RSV), where the search engine was used between April and Sept 2001. One million queries were made by the public. Of these queries 10 percent were "misspelled" or erroneous and our spell checker corrected around 90 percent of these.