DocumentCode :
2625681
Title :
Dataset Retrieval
Author :
Kunze, Sven R. ; Auer, Stefan
Author_Institution :
Dept. of Comput. Sci., Chemnitz Univ. of Technol., Chemnitz, Germany
fYear :
2013
fDate :
16-18 Sept. 2013
Firstpage :
1
Lastpage :
8
Abstract :
Recently, a large number of dataset repositories, catalogs and portals are emerging in the science and government realms. Once a large number of datasets are published on such data portals, the question arises how to retrieve datasets satisfying an information need. In this paper, we present an approach for retrieving datasets according to user queries. We define dataset retrieval as a specialization of information retrieval. Instead of retrieving documents that are relevant to a certain information need, dataset retrieval describes the process of returning relevant RDF datasets. As with information retrieval, the term relevance cannot be clearly defined when using traditional methods like stemming. The inherent usage of RDF in these datasets enables a better way of retrieving relevant ones. We therefore propose an additional retrieval mechanism, which is inspired by facet search: dataset filtering. When querying, the entire set of available datasets is processed by a set of semantic filters each of which can unambiguously decide whether or not a given dataset is relevant to the query. The resulting set is then given back to the requester. We implemented and evaluated our approach in CKAN, which fuels publicdata.eu and is the most popular data portal worldwide.
Keywords :
information filtering; information needs; query processing; relevance feedback; CKAN; RDF datasets; catalogs; data portals; dataset filtering; dataset repositories; dataset retrieval; facet search; information need; information retrieval; semantic filters; term relevance; user queries; Catalogs; Companies; Portals; Resource description framework; Semantics; Vocabulary; RDF; VoID; dataset filtering; dataset repository; dataset retrieval; information retrieval; similarity relation; vocabulary;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Semantic Computing (ICSC), 2013 IEEE Seventh International Conference on
Conference_Location :
Irvine, CA
Type :
conf
DOI :
10.1109/ICSC.2013.12
Filename :
6693487
Link To Document :
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