matchning

Matchning, or matching, is the process of establishing correspondences between two or more sets of items according to criteria such as similarity, compatibility, or relevance. It is used to pair, align, or identify records, agents, resources, or signals across domains. The term appears in data management, mathematics, economics, computer science, and linguistics.

In data management, matching refers to entity resolution or deduplication, where records that describe the same real-world entity are linked across datasets. Methods are deterministic (fields must match exactly) or probabilistic (likelihood-based). Techniques include blocking to reduce comparisons and similarity measures such as Jaccard, cosine, Levenshtein distance, and custom rules. Challenges include misspellings, changes over time, and incomplete data.

In graph theory, a matching is a set of edges with no shared vertices. A maximum matching has the largest possible number of edges; a perfect matching covers all vertices. Algorithms include the Edmonds blossom algorithm for general graphs and Hopcroft–Karp for bipartite graphs.

In economics and market design, matching markets pair participants (for example job seekers and firms, or donors and recipients) when prices do not clear efficiently. Mechanisms such as the deferred acceptance algorithm aim to produce stable matchings that respect preferences and capacity constraints. Applications include school choice, organ exchange, and labor markets.

Other uses of the term appear in computing, where pattern matching decomposes data according to predefined structures, and in recommender systems and advertising, where matching aligns users with items or ads based on preferences or signals.