wordrovnání

Wordrovnání is a term used in linguistics and information science to describe procedures that compare words or lexical units to determine whether they are equal or similar. It covers both exact matches, where two tokens are identical after normalization, and fuzzy matches, which allow for differences in spelling, morphology, or diacritics. The concept is applied in natural language processing, information retrieval, and text processing to judge lexical similarity, support disambiguation of forms, and assist in data cleansing and search tasks.

Techniques in wordrovnání include preprocessing steps such as case normalization, diacritic removal, and handling of whitespace and punctuation, as well as morphological normalization through stemming or lemmatization. The comparison itself relies on distance or similarity measures, such as Levenshtein (edit) distance, Damerau-Levenshtein distance, Jaro-Winkler, or vector-based methods like cosine similarity on character or word n-grams. Phonetic algorithms may be used in some applications to capture phonetic similarity.

Applications of wordrovnání are broad. They include spell checking and autocorrection, fuzzy search and query expansion, deduplication and record linkage, OCR post-processing, translation memory alignment, and plagiarism detection. In each case, the goal is to determine whether different word forms refer to the same underlying unit or to related units.

Language-specific challenges arise in morphologically rich languages, where extensive inflection, diacritics, and homonymy complicate direct comparisons. Effective wordrovnání in such languages often combines lemmatization with language-aware similarity measures to avoid conflating distinct lemmas or senses.

Wordrovnání is related to broader concepts such as string similarity, normalization, and data cleansing, and it is typically implemented as a module within NLP pipelines that supports higher-level tasks like search ranking and textual analysis.