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IBEX: Harvesting Entities from the Web Using Unique Identifiers

Published: 31 May 2015 Publication History

Abstract

In this paper we study the prevalence of unique entity identifiers on the Web. These are, e.g., ISBNs (for books), GTINs (for commercial products), DOIs (for documents), email addresses, and others. We show how these identifiers can be harvested systematically from Web pages, and how they can be associated with humanreadable names for the entities at large scale.
Starting with a simple extraction of identifiers and names from Web pages, we show how we can use the properties of unique identifiers to filter out noise and clean up the extraction result on the entire corpus. The end result is a database of millions of uniquely identified entities of different types, with an accuracy of 73--96% and a very high coverage compared to existing knowledge bases. We use this database to compute novel statistics on the presence of products, people, and other entities on the Web.

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cover image ACM Conferences
WebDB'15: Proceedings of the 18th International Workshop on Web and Databases
May 2015
75 pages
ISBN:9781450336277
DOI:10.1145/2767109
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 31 May 2015

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  • Research-article
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SIGMOD/PODS'15
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SIGMOD/PODS'15: International Conference on Management of Data
May 31 - June 4, 2015
VIC, Melbourne, Australia

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WebDB'15 Paper Acceptance Rate 9 of 31 submissions, 29%;
Overall Acceptance Rate 30 of 100 submissions, 30%

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  • (2019)Company Acquisition Relations Extraction From Web PagesSemantic Web Science and Real-World Applications10.4018/978-1-5225-7186-5.ch001(1-17)Online publication date: 2019
  • (2019)Knowledge Harvesting: Achievements and ChallengesComputing and Software Science10.1007/978-3-319-91908-9_13(217-235)Online publication date: 2019
  • (2018)Synthesizing Type-Detection Logic for Rich Semantic Data Types using Open-source CodeProceedings of the 2018 International Conference on Management of Data10.1145/3183713.3196888(35-50)Online publication date: 27-May-2018
  • (2016)YAGO: A Multilingual Knowledge Base from Wikipedia, Wordnet, and GeonamesThe Semantic Web – ISWC 201610.1007/978-3-319-46547-0_19(177-185)Online publication date: 23-Sep-2016

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