This paper presents a survey of schema-based matching approaches. The authors classify schema-based matching techniques based on their input, process, and output dimensions. They distinguish between approximate and exact techniques at the schema level, and between syntactic, semantic, and external techniques at the element- and structure-level. The authors also discuss the differences between schema and ontology matching, and the importance of matching in various application domains such as information integration, data warehousing, and web services. The paper provides an overview of recent schema/ontology matching systems and their capabilities. The authors propose a new classification of schema-based matching techniques that builds on previous work and introduces new criteria based on general properties of matching techniques, interpretation of input information, and the kind of input information. The classification is used to compare existing matching systems and to design new ones. The paper also discusses various matching techniques, including string-based, language-based, constraint-based, and semantic techniques, as well as graph-based, taxonomy-based, and model-based techniques. The authors conclude that schema-based matching is an important area of research with many applications in various domains.This paper presents a survey of schema-based matching approaches. The authors classify schema-based matching techniques based on their input, process, and output dimensions. They distinguish between approximate and exact techniques at the schema level, and between syntactic, semantic, and external techniques at the element- and structure-level. The authors also discuss the differences between schema and ontology matching, and the importance of matching in various application domains such as information integration, data warehousing, and web services. The paper provides an overview of recent schema/ontology matching systems and their capabilities. The authors propose a new classification of schema-based matching techniques that builds on previous work and introduces new criteria based on general properties of matching techniques, interpretation of input information, and the kind of input information. The classification is used to compare existing matching systems and to design new ones. The paper also discusses various matching techniques, including string-based, language-based, constraint-based, and semantic techniques, as well as graph-based, taxonomy-based, and model-based techniques. The authors conclude that schema-based matching is an important area of research with many applications in various domains.