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- 175 creator andrea-giovanni-nuzzolese.
- 175 creator angelo-di-iorio.
- 175 creator fabio-vitali.
- 175 creator paolo-ciancarini.
- 175 creator silvio-peroni.
- 175 type InProceedings.
- 175 label "Evaluating citation functions in CiTO: cognitive issues".
- 175 sameAs 175.
- 175 abstract "Networks of citations are a key tool for referencing, disseminating and evaluating research results. The task of characterising the functional role of citations in scientific literature is very difficult, not only for software agents but for humans, too. The main problem is that the mental models of different annotators hardly ever converge to a single shared opinion. The goal of this paper is to investigate how an existing reference model for classifying citations, namely CiTO (Citation Typing Ontology), is interpreted and used by annotators of scientific literature. We present some experiments capturing the cognitive processes behind users' decisions in annotating papers with CITO, and provide initial ideas to refine future releases of CiTO and to simulate readers' behaviour within CiTaLO, a tool for automatic classification of citations.".
- 175 hasAuthorList authorList.
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- 175 keyword "CiTO".
- 175 keyword "citation functions".
- 175 keyword "human inter-rater agreement".
- 175 keyword "mental models".
- 175 keyword "usability".
- 175 keyword "user testing session".
- 175 title "Evaluating citation functions in CiTO: cognitive issues".
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- 192 creator andreas-harth.
- 192 creator basil-ell.
- 192 creator elena-simperl.
- 192 type InProceedings.
- 192 label "SPARQL Query Verbalization for Explaining Semantic Search Engine Queries".
- 192 sameAs 192.
- 192 abstract "In this paper we introduce Spartiqulation, a system that translates SPARQL queries into English text. Our aim is to allow casual end users of semantic applications with limited to no expertise in the SPARQL query language to interact with these applications in a more intuitive way. The verbalization approach exploits domain-independent template-based natural language generation techniques, as well as linguistic cues in labels and URIs.".
- 192 hasAuthorList authorList.
- 192 isPartOf proceedings.
- 192 keyword "Natural Language Generation".
- 192 keyword "Natural Language Interfaces".
- 192 keyword "SPARQL verbalization".
- 192 title "SPARQL Query Verbalization for Explaining Semantic Search Engine Queries".
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- 20 creator hugh-c-davis.
- 20 creator thanassis-tiropanis.
- 20 creator xin-wang.
- 20 type InProceedings.
- 20 label "Optimising Linked Data Queries Using Runtime Statistics in the Presence of Co-reference".
- 20 sameAs 20.
- 20 abstract "Due to the distributed nature of Linked Data, many resources are referred to by more than one URI. This phenomenon, known as co-reference, increases the probability of leaving out implicit semantically related results when querying Linked Data. The probability of co-reference increases further when considering distributed SPARQL queries over a larger set of distributed datasets. Addressing co-reference in Linked Data queries, on one hand, increases complexity of query processing. On the other hand, it requires changes in how statistics of datasets are taken into consideration. We investigate these two challenges of addressing co-reference in distributed SPARQL queries, and propose two methods to improve query efficiency: 1) a model named Virtual Graph, that transforms a query with co-reference into a normal query with pre-existing bindings; 2) an algorithm named $\Psi$, that intensively exploits parallelism, and dynamically optimises queries using runtime statistics. We deploy both methods in an distributed engine called LHD-d. To evaluate LHD-d, we investigate the distribution of co-reference in the real world, based on which we simulate an experimental RDF network. In this environment we demonstrate the advantages of LHD-d for distributed SPARQL queries in environments with co-reference.".
- 20 hasAuthorList authorList.
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- 20 keyword "Linked Data".
- 20 keyword "SPARQL".
- 20 keyword "co-reference".
- 20 keyword "distributed query".
- 20 keyword "dynamic optimisation".
- 20 title "Optimising Linked Data Queries Using Runtime Statistics in the Presence of Co-reference".
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