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The Mannheim Search Join Engine

11 Pages Posted: 6 Jul 2018 First Look: Accepted

See all articles by Oliver Lehmberg

Oliver Lehmberg

University of Mannheim - Data and Web Science Group

Dominique Ritze

University of Mannheim - Data and Web Science Group

Petar Ristoski

University of Mannheim - Data and Web Science Group

Robert Meusel

University of Mannheim - Data and Web Science Group

Heiko Paulheim

University of Mannheim - Data and Web Science Group

Christian Bizer

University of Mannheim - Data and Web Science Group

Abstract

A Search Join is a join operation which extends a user-provided table with additional attributes based on a large corpus of heterogeneous data originating from the Web or corporate intranets. Search Joins are useful within a wide range of application scenarios: Imagine you are an analyst having a local table describing companies and you wan to extend this table with attributes containing the headquarters, turnover, and revenue of each company. Or imagine you are a film enthusiast and want to extend a table describing films with attributes like director, genre, and release date of each film. This article presents the Mannheim Search Join Engine which automatically performs such table extension operations based on a large corpus of Web data. Given a local table, the Mannheim Search Join Engine searches the corpus for additional data describing the entities contained in the input table. The discovered data is then joined with the local table and is consolidated using schema matching and data fusion techniques. As result, the user is presented with an extended table and given the opportunity to examine the provenance of the added data. We evaluate the Mannheim Search Join Engine using heterogeneous data originating from over one million different websites. The data corpus consists of HTML tables, as well as Linked Data and Microdata annotations which are converted into tabular form. Our experiments show that the Mannheim Search Join Engine achieves a coverage close to 100% and a precision of around 90% for the tasks of extending tables describing cities, companies, countries, drugs, books, films, and songs.

Keywords: Table Extension, Data Search, Search Joins, Web Tables, Microdata, Linked Data

Suggested Citation

Lehmberg, Oliver and Ritze, Dominique and Ristoski, Petar and Meusel, Robert and Paulheim, Heiko and Bizer, Christian, The Mannheim Search Join Engine (2015). Journal of Web Semantics First Look. Available at SSRN: https://ssrn.com/abstract=3198928 or http://dx.doi.org/10.2139/ssrn.3198928

Oliver Lehmberg (Contact Author)

University of Mannheim - Data and Web Science Group ( email )

L 5, 2 - 2. OG
68161 Mannheim
Germany

Dominique Ritze

University of Mannheim - Data and Web Science Group ( email )

L 5, 2 - 2. OG
68161 Mannheim
Germany

Petar Ristoski

University of Mannheim - Data and Web Science Group ( email )

L 5, 2 - 2. OG
68161 Mannheim
Germany

Robert Meusel

University of Mannheim - Data and Web Science Group ( email )

L 5, 2 - 2. OG
68161 Mannheim
Germany

Heiko Paulheim

University of Mannheim - Data and Web Science Group ( email )

L 5, 2 - 2. OG
68161 Mannheim
Germany

Christian Bizer

University of Mannheim - Data and Web Science Group

L 5, 2 - 2. OG
68161 Mannheim
Germany

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