This paper accounts for a new technique of correcting isolated words in typed texts. A language-dependent set of string substitutions reflects the surface form of errors that result from vocabulary incompetence, misspellings, or mistypings. Candidate corrections are formed by applying the substitutions to text words absent from the computer lexicon. A minimal acyclic deterministic finite automaton storing the lexicon allows quick rejection of nonsense corrections, while costs associated with the substitutions serve to rank the remaining ones. A comparison of the correction lists generated by several spellcheckers for two corpora of English spelling errors shows that our technique suggests the right words more accurately than the others.

Abstract. A major issue when defining the efficiency of a spelling corrector is how far we need to examine the input string to validate the repairs. We claim that regional techniques provide a performance and quality comparable to that attained by global criteria, with a significant saving in time and space. 1

Abstract. We focus on the domain of a regional least-cost strategy in order to illustrate the viability of non-global repair models over finitestate architectures. Our interest is justified by the difficulty, shared by all repair proposals, to determine how far to validate. A short validation may fail to gather sufficient information, and in a long one most of the effort can be wasted. The goal is to prove that our approach can provide, in practice, a performance and quality comparable to that attained by global criteria, with a significant saving in time and space. To the best of our knowledge, this is the first discussion of its kind. 1

In this paper, we propose and evaluate two different alternatives to deal with degraded queries on Spanish ir applications. The first one is an n-gram-based strategy which has no dependence on the degree of available linguistic knowledge. On the other hand, we propose two spelling correction techniques, one of which has a strong dependence on a stochastic model that must be previously built from a POStagged corpus. In order to study their validity, a testing framework has been formally designed and applied on both approaches.

Abstract. Our work relies on the design and evaluation of experimental information retrieval systems able to cope with textual misspellings in queries. In contrast to previous proposals, commonly based on the consideration of spelling correction strategies and a word language model, we also report on the use of character n-grams as indexing support. Key words: Degraded text, information retrieval 1