Abstract: A query word is used to identify one of a number of word groups, by first determining whether the query word is in any of the word groups. If not, attempts to modify the query word are made in accordance with successive suffix relationships in a sequence until a modified query word is obtained that is in one of the word groups. The sequence of suffix relationships, which can be pairwise relationships, can be defined by a list ordered according to the frequencies of occurrence of the suffix relationships in a natural language. If a modified query word is obtained that is in one of the word groups, information identifying the word group can be provided, such as a representative of the group or a list of words in the group.

Abstract: To provide information about the meaning of a multi-token expression in a first language, where the information is understandable in a second language, subexpressions are obtained, such as tokens, chunks, and sentences. The multi-token expression could, for example, be a sentence or an input text with more than one sentence. Translation choices are obtained in the second language for a set of the subexpressions. A subset of the translation choices of a subexpression are ranked, and the ranked translation choices are used to produce a sequence of translation choices for the multi-token expression as a whole. Information is then presented to a user about the sequence of translation choices, indicating in the second language the meaning of the multi-token expression. Translation choices can be ranked based on syntactic or semantic context, based on translation source, based on confidence levels, based on how each was obtained, in accordance with a user-selected process, and so forth.

Abstract: A set of words of a natural language is grouped by automatically obtaining suffix relation data that indicate a relation value for each of a set of relationships between suffixes that occur in the natural language, and, then, by automatically clustering the words in the set using the relation values from the suffix relation data, to obtain group data indicating groups of words. Two or more words in a group have suffixes as in one of the relationships and, preceding the suffixes, equivalent substrings. The relationships can be pairwise relationships, and the relation value can indicate the number of occurrences of a suffix pair. The suffix relation data can be obtained using an inflectional lexicon. Complete link clustering can be used.

Abstract: Selected character strings are automatically found by performing an automatic search of a text to find character strings that match any of a list of selected strings. The automatic search includes a series of iterations, each with a starting point in the text. Each iteration determines whether its starting point is followed by a character string that matches any of the list of selected strings and that ends at a probable string ending. Each iteration also finds a starting point for the next iteration that is a probable string beginning. The selected strings can be words and multiple word expressions, in which case probable string endings and beginnings are word boundaries. A finite state lexicon, such as a finite state transducer or a finite state automation, can be used to determine whether character strings match the list of selected strings. A tokenizing automation can be used to find starting points.