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![Global Detection
Duplicate detection, also known as entity resolution,
record linkage, or reference reconciliation is a well-
studied problem and an active research area. [Tutorial-
VLDB’05, Tutorial-SIGMOD’06]
We use existing declarative techniques [D.App.σ-SIGMOD’07]
to detect duplicates across multiple files.
Display disambiguation page on HTML interface and
rdfs:seeAlso attribute on RDF interface.
Also enables user to provide feedback by
@string{vldb = Very Large Data Base}](https://image.slidesharecdn.com/bibbaseldtc2010presentation-101125150001-phpapp02/85/BibBase-Linked-Data-Triplification-Challenge-2010-Presentation-11-320.jpg)
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BibBase Linked Data Triplification Challenge 2010 Presentation
- 1. BibBase Triplified http://data.bibbase.org/ Presentedby: Reynold S. Xin UC Berkeley Joint work with: Oktie Hassanzadeh, Yang Yang, Jiang Du, Minghua Zhao, Renee J. Miller University of Toronto Christian Fritz University of Southern California
- 2. Outline Goals andStatus Duplicate detection Interlinking of data sources Additional features Conclusions and future work
- 5. Goals http://www.bibbase.org Makesit easy for scientists to maintain publications pages Scientists maintain a bibtex file; BibBase does the rest Publishes them in HTML
- 6. Goals http://data.bibbase.org Makesit easy for scientists to maintain publications pages Scientists maintain a bibtex file; BibBase does the rest Publishes them in HTML Publishes them in RDF Links entries to the open linked data cloud With incentive, scientists are helping us build a bibliographic database (think DBLP but automated) Invaluable data set for benchmarking duplicate detection and semantic link discovery systems
- 8. Some statistics “Beta”went online in June 2010 As of yesterday (September 1, 2010) ~ 100 active users 4520 publications, 4883 authors, 502 journals, 1881 proceedings, 88 keywords 39201 author links, 2768 publication links, 30 keyword links Note that this is before we do any form of “marketing”
- 9. Duplicate Detection Examples Authors: “Renee J. Miller” or “R. J. Miller” or “RJ Miller” Publication entries Journal & conferences: “VLDB” or “Very Large Data Base” Solutions Local detection (within a single bibtex file) Global detection (across multiple files)
- 10. Local Detection Aset of predefined rules to identify duplicates. E.g. within a single file, it is highly likely that “Renee J Miller” is the same as “RJ Miller”. Users can specify a suffix to the name to differentiate them (DBLP approach). E.g. “Min Wang” vs “Min Wang2”
- 11. Global Detection Duplicatedetection, also known as entity resolution, record linkage, or reference reconciliation is a well- studied problem and an active research area. [Tutorial- VLDB’05, Tutorial-SIGMOD’06] We use existing declarative techniques [D.App.σ-SIGMOD’07] to detect duplicates across multiple files. Display disambiguation page on HTML interface and rdfs:seeAlso attribute on RDF interface. Also enables user to provide feedback by @string{vldb = Very Large Data Base}
- 12. Interlinking of DataSources Leverages both offline dictionaries and online real-time URL verifications. Some external data sources DBLP DBpedia RKBExplorer Semantic Web Dogfood LOD foaf
- 13. Additional Features Storageand publication of provenance information Dynamic grouping of entities (by year, keyword, etc) RSS feed for notification DBLP scraper to generate bibtex files from DBLP records Statistics on usage Enhancement to existing MIT bibtex ontology file
- 14. Conclusion and FutureWork BibBase Light-weight publication of bibliographic data Semantic web technologies as a result of complex triplification performed inside the system Invaluable data set Future Work More comprehensive duplicate detection Links to more external data sources Better engineering and service level agreement (99.99%?) Broader user base
- 15.