Learn More
We present a novel framework for mapping between any combination of XML and rela-tional schemas, in which a high-level, user-specified mapping is translated into semantically meaningful queries that transform source data into the target representation. Our approach works in two phases. In the first phase, the high-level mapping, expressed as a set of(More)
A fundamental problem in information integration is to precisely specify the relationships, called mappings, between schemas. Designing mappings is a time-consuming process. To alleviate this problem, many mapping systems have been developed to assist the design of mappings. However, a benchmark for comparing and evaluating these systems has not yet been(More)
In dynamic environments like the Web, data sources may change not only their data but also their schemas, their semantics, and their query capabilities. When a mapping is left inconsistent by a schema change, it has to be detected and updated. We present a novel framework and a tool (ToMAS) for automatically adapting (rewriting) mappings as schemas evolve.(More)
The Clio project provides tools that vastly simplify information integration. Information integration requires data conversions to bring data in different representations into a common form. Key contributions of Clio are the definition of non-procedural schema mappings to describe the relationship between data in heterogeneous schemas, a new paradigm in(More)
There is a growing need to associate a variety of metadata with the underlying data, but a simple, elegant approach to uniformly model and query both the data and the metadata has been elusive. In this paper, we argue that (1) the relational model augmented with queries as data values is a natural way to uniformly model data, arbitrary metadata and their(More)
Keyword queries offer a convenient alternative to traditional SQL in querying relational databases with large, often unknown, schemas and instances. The challenge in answering such queries is to discover their intended semantics, construct the SQL queries that describe them and used them to retrieve the respective tuples. Existing approaches typically rely(More)
Entity linkage is central to almost every data integration and data cleaning scenario. Traditional techniques use some computed similarity among data structure to perform merges and then answer queries on the merged data. We describe a novel framework for entity linkage with uncertainty. Instead of using the linkage information to merge structures a-priori,(More)
Search engines are continuously employing advanced techniques that aim to capture user intentions and provide results that go beyond the data that simply satisfy the query conditions. Examples include the personalized results, related searches, similarity search, popular and relaxed queries. In this work we introduce a novel query paradigm that considers a(More)