Real-time RDF extraction from unstructured data streams
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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The Semantic Web, ISWC 2013: 12th International Semantic Web Conference, Proceedings. ed. / Harith Alani; Lalana Kagal; Achille Fokoue; Paul Groth; Chris Biemann; Josiane Xavier Parreira; Lora Aroyo; Natasha Noy; Chris Welty; Krzyztof Janowicz. Springer Verlag, 2013. p. 135-150 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8218 LNCS, No. PART 1).
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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TY - CHAP
T1 - Real-time RDF extraction from unstructured data streams
AU - Gerber, Daniel
AU - Hellmann, Sebastian
AU - Bühmann, Lorenz
AU - Soru, Tommaso
AU - Usbeck, Ricardo
AU - Ngonga Ngomo, Axel Cyrille
PY - 2013
Y1 - 2013
N2 - The vision behind the Web of Data is to extend the current document-oriented Web with machine-readable facts and structured data, thus creating a representation of general knowledge. However, most of the Web of Data is limited to being a large compendium of encyclopedic knowledge describing entities. A huge challenge, the timely and massive extraction of RDF facts from unstructured data, has remained open so far. The availability of such knowledge on the Web of Data would provide significant benefits to manifold applications including news retrieval, sentiment analysis and business intelligence. In this paper, we address the problem of the actuality of the Web of Data by presenting an approach that allows extracting RDF triples from unstructured data streams. We employ statistical methods in combination with deduplication, disambiguation and unsupervised as well as supervised machine learning techniques to create a knowledge base that reflects the content of the input streams. We evaluate a sample of the RDF we generate against a large corpus of news streams and show that we achieve a precision of more than 85%.
AB - The vision behind the Web of Data is to extend the current document-oriented Web with machine-readable facts and structured data, thus creating a representation of general knowledge. However, most of the Web of Data is limited to being a large compendium of encyclopedic knowledge describing entities. A huge challenge, the timely and massive extraction of RDF facts from unstructured data, has remained open so far. The availability of such knowledge on the Web of Data would provide significant benefits to manifold applications including news retrieval, sentiment analysis and business intelligence. In this paper, we address the problem of the actuality of the Web of Data by presenting an approach that allows extracting RDF triples from unstructured data streams. We employ statistical methods in combination with deduplication, disambiguation and unsupervised as well as supervised machine learning techniques to create a knowledge base that reflects the content of the input streams. We evaluate a sample of the RDF we generate against a large corpus of news streams and show that we achieve a precision of more than 85%.
KW - Informatics
KW - Time Slice
KW - Name Entry Recognition
KW - Pattern Mapping
KW - Link Open Data
KW - String Similarity
KW - Business informatics
UR - http://www.scopus.com/inward/record.url?scp=84891950965&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/5d304550-be6f-361f-8bc5-05940fd2117e/
U2 - 10.1007/978-3-642-41335-3_9
DO - 10.1007/978-3-642-41335-3_9
M3 - Article in conference proceedings
AN - SCOPUS:84891950965
SN - 9783642413346
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 135
EP - 150
BT - The Semantic Web, ISWC 2013
A2 - Alani, Harith
A2 - Kagal, Lalana
A2 - Fokoue, Achille
A2 - Groth, Paul
A2 - Biemann, Chris
A2 - Parreira, Josiane Xavier
A2 - Aroyo, Lora
A2 - Noy, Natasha
A2 - Welty, Chris
A2 - Janowicz, Krzyztof
PB - Springer Verlag
T2 - 12th International Semantic Web Conference, ISWC 2013
Y2 - 21 October 2013 through 25 October 2013
ER -