Schema mapping discovery from data instances

Schema Mapping as Query Discovery

Discovery and Correctness of Schema Mapping Transformations

Schema mapping is becoming pervasive in all data transformation, exchange and integration tasks. It brings to the surface the problem of differences and mismatches between heterogeneous formats and models, respectively used in source and target databases to be mapped one to another. In this chapter, we start by describing the problem of schema mapping, its background and technical implications....

Schema Discovery for Semistructured Data

To formulate a meaningful query on semistructured data, such as on the Web, that matches some of the source’s structure, we need first to discover something about how the information is represented in the source. This is referred to as schema discovery and was considered for a single object recently. In the case of multiple objects, the task of schema discovery is to identify typical structurin...

Navigating Extracted Data with Schema Discovery

Open Information Extraction (OIE) is a recently-introduced type of information extraction that extracts small individual pieces of data from input text without any domainspecific guidance such as special training data or extraction rules. For example, an OIE system might discover the triple Frenzy, year, 1972 from a set of documents about movies. Because OIE is domain-independent, it promises t...

Discovery of temporal patterns from process instances

Existing work in process mining focuses on the discovery of the underlying process model from their instances. In this paper, we do not assume the existence of a single process model to which all process instances comply, and the goal is to discover a set of frequently occurring temporal patterns. Discovery of temporal patterns can be applied to various application domains to support crucial bu...