Combining linked data and statistical information retrieval: Next generation information systems
Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
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Combining linked data and statistical information retrieval : Next generation information systems. / Usbeck, Ricardo.
The Semantic Web: Trends and Challenges - 11th International Conference, ESWC 2014, Proceedings. Hrsg. / Valentina Presutti; Claudia d'Amato; Fabien Gandon; Matthieu d'Aquin; Steffen Staab; Anna Tordai. Springer-Verlag Wien, 2014. S. 845-854 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 8465 LNCS).Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
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RIS
TY - CHAP
T1 - Combining linked data and statistical information retrieval
T2 - 11th International Conference on Semantic Web: Trends and Challenges
AU - Usbeck, Ricardo
N1 - Conference code: 11
PY - 2014/1/1
Y1 - 2014/1/1
N2 - Being a part of the Information Age, users are challenged with a tremendously growing amount of Web data which generates a need for more sophisticated information retrieval systems. The Semantic Web provides necessary procedures to augment the highly unstructured Web with suitable metadata in order to leverage search quality and user experience. In this article, we will outline an approach for creating a web-scale, precise and efficient information system capable of understanding keyword, entity and natural language queries. By using Semantic Web methods and Linked Data the doctoral work will present how the underlying knowledge is created and elaborated searches can be performed on top.
AB - Being a part of the Information Age, users are challenged with a tremendously growing amount of Web data which generates a need for more sophisticated information retrieval systems. The Semantic Web provides necessary procedures to augment the highly unstructured Web with suitable metadata in order to leverage search quality and user experience. In this article, we will outline an approach for creating a web-scale, precise and efficient information system capable of understanding keyword, entity and natural language queries. By using Semantic Web methods and Linked Data the doctoral work will present how the underlying knowledge is created and elaborated searches can be performed on top.
KW - NLP
KW - Question Answering
KW - Ranking
KW - Search
KW - Informatics
KW - Business informatics
UR - http://www.scopus.com/inward/record.url?scp=84902590463&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/c43cd624-fd54-3e10-a595-ca3c73847ac8/
U2 - 10.1007/978-3-319-07443-6_58
DO - 10.1007/978-3-319-07443-6_58
M3 - Article in conference proceedings
AN - SCOPUS:84902590463
SN - 978-3-319-07442-9
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 845
EP - 854
BT - The Semantic Web
A2 - Presutti, Valentina
A2 - d'Amato, Claudia
A2 - Gandon, Fabien
A2 - d'Aquin, Matthieu
A2 - Staab, Steffen
A2 - Tordai, Anna
PB - Springer-Verlag Wien
Y2 - 25 May 2014 through 29 May 2014
ER -