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- item-1 hasContent alice-hermann.
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- item-3 hasContent mireille-ducasse.
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- 37 creator gerd-groener.
- 37 creator matthias-thimm.
- 37 creator renata-dividino.
- 37 creator stefan-scheglmann.
- 37 type InProceedings.
- 37 label "Ranking RDF with Provenance via Preference Aggregation".
- 37 sameAs 37.
- 37 abstract "Information retrieval on RDF data benefits greatly from additional provenance information attached to the individual pieces of information. Currently, provenance information such as source, certainty, and temporal information on RDF statements can be used to rank search results according to one of those dimensions. In this paper, we consider the problem of aggregating provenance information from different dimensions in order to obtain a joint ranking over all dimensions. We relate this problem to the problem of preference aggregation in social choice theory and translate different solutions for preference aggregation to the problem of aggregating provenance rankings. By exploiting the algebraic structure of provenance rankings we characterize three different approaches for aggregating preferences, namely the lexicographical rule, the Borda rule and the plurality rule, in our framework of provenance aggregation.".
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- 37 title "Ranking RDF with Provenance via Preference Aggregation".
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- item-1 hasContent renata-dividino.
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- item-2 hasContent gerd-groener.
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- item-4 hasContent matthias-thimm.
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- 4 creator c-maria-keet.
- 4 creator zubeida-khan.
- 4 type InProceedings.
- 4 label "ONSET: Automated Foundational Ontology Selection and Explanation".
- 4 sameAs 4.
- 4 abstract "Using a foundational ontology for domain ontology development is beneficial in theory and practice. However, developers have difficulty with choosing the appropriate foundational ontology, and why. In order to solve this problem, a comprehensive set of criteria that influence foundational ontology selection has been compiled and the values for each parameter determined for DOLCE, BFO, GFO, and SUMO. This paper-based analysis is transformed into an easily extensible algorithm and implemented in the novel tool ONSET, which helps a domain ontology developer to choose a foundational ontology through interactive selection of preferences and scaling of importance so that it computes the most suitable foundational ontology for the domain ontology and explains why this selection was made. This has been evaluated in an experiment with novice modellers, which showed that ONSET greatly assists in foundational ontology selection.".
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- 4 title "ONSET: Automated Foundational Ontology Selection and Explanation".
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- 53 creator giovanni-tummarello.
- 53 creator renaud-delbru.
- 53 creator stephane-campinas.
- 53 type InProceedings.
- 53 label "Effective Retrieval Model for Entity with Multi-Valued Attributes: BM25MF and Beyond".
- 53 sameAs 53.
- 53 abstract "The task of entity retrieval becomes increasingly prevalent as more and more structured information about entities is available on the Web in various forms such as documents embedding metadata (RDF, RDFa, Microdata, Microformats). The amount of structured data is such that supporting an effective search and discovery of entities is crucial for ensuring a satisfying user experience. Indeed, this need is reflected by international benchmarking campaigns, such as the Text REtrieval Conference or the Semantic Search Challenge which propose entity-oriented search tracks. In this work, we present a multi-valued attribute model for entity retrieval which extends and generalises existing field-based ranking models. Our model introduces the concept of multi-valued attributes and enables attribute and value specific normalization and weighting. We extend based on our model two state-of-the-art field-based rankings, i.e., BM25F and PL2F, and demonstrate that our model improves significantly the retrieval performance compared to existing models through evaluations on heterogeneous datasets. Finally, we introduce query dependent and independent weights specifically designed for our model which provide significant performance improvement.".
- 53 hasAuthorList authorList.
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- 53 title "Effective Retrieval Model for Entity with Multi-Valued Attributes: BM25MF and Beyond".
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- item-1 hasContent stephane-campinas.
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- item-2 hasContent renaud-delbru.
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- item-3 hasContent giovanni-tummarello.
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- 55 creator jens-lehmann.
- 55 creator lorenz-buehmann.
- 55 type InProceedings.
- 55 label "Universal OWL Axiom Enrichment for Large Knowledge Bases".
- 55 sameAs 55.
- 55 abstract "The Semantic Web has seen a rise in the availability and usage of knowledge bases over the past years, in particular in the Linked Open Data initiative. Despite this growth, there is still a lack of knowledge bases that consist of high quality schema information and instance data adhering to this schema. Several knowledge bases only consist of schema information, while others are, to a large extent, a mere collection of facts without a clear structure. The combination of rich schema and instance data would allow powerful reasoning, consistency checking, and improved querying possibilities as well as provide more generic ways to interact with the underlying data. In this article, we present a light-weight method to enrich knowledge bases accessible via SPARQL endpoints with almost all types of OWL 2 axioms. This allows to semi-automatically create schemata, which we evaluate and discuss using DBpedia.".
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- 55 title "Universal OWL Axiom Enrichment for Large Knowledge Bases".
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