Likemäärata

Likemäärata is a term used in Estonian-language contexts to describe the process of determining the degree of similarity or likelihood between two objects, records, or events. In practice, likemäärata encompasses methods that assign a numerical score reflecting how alike two items are, or how likely it is that they belong to the same category or real-world entity.

Etymology and scope: The word is formed from Estonian roots that convey similarity and determination. As a concept, likemäärata spans methods from simple rule-based checks to formal statistical and machine-learning approaches used to quantify likeness.

Methods and metrics: Common approaches include feature-based similarity metrics such as cosine similarity for vector representations, Jaccard similarity for sets, and probabilistic models that compute likelihoods under a specified hypothesis. In data management, likemäärata is closely related to record linkage and deduplication, where fields like name, address, and date of birth are used to estimate whether two records refer to the same real-world entity. In machine learning, learned similarity functions can be trained with labeled pairs to improve accuracy.

Applications and limitations: Likemäärata is applied in data cleaning, duplicate detection, recommender systems, and various text, image, and bioinformatics similarity tasks. Limitations include dependence on feature representation, data quality, missing values, and the choice of similarity thresholds, which can affect precision and recall. Ethical considerations involve potential misidentification and privacy concerns when linking or comparing sensitive information.

See also: similarity measure, record linkage, deduplication, pattern recognition, clustering.