A Relaxed Approach to RDF Querying

Hurtado, Claudia; Poulovassilis, Alexandra; Wood, Peter T.

doi:10.1007/11926078_23

Cited by 25 publications

(16 citation statements)

References 9 publications

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“…Hurtado et al in [15] propose two kinds of relaxation for triple pattern which exploit RDF entailment to relax the queries.…”

Section: Query Relaxation Modelmentioning

confidence: 99%

“…Given a user query Q and its relaxed queries Q 1 and Q 2 , if Q 1 is ranked prior to Q 2 , then we return the answers of Q 1 prior to the answers of Q 2 . In [15], the authors introduced a ranking model for the relaxed queries. Given two relaxed queries of the user query, if one is subsumed by the other, then the former relaxed query is better.…”

Section: Ranking Modelmentioning

confidence: 99%

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Approximating query answering on RDF databases

2011

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Database users may be frustrated by no answers returned when they pose a query on the database. In this paper, we study the problem of relaxing queries on RDF databases in order to acquire approximate answers. We address two problems in efficient query relaxation. First, to ensure the quality of answers, we compute the similarities between relaxed queries with regard to the user query and use them to score the potential relevant answers. Second, for obtaining top-k answers, we develop two algorithms. One is based on the best-first strategy and relaxed queries are executed in the ranking order. The batch based algorithm executes the relaxed queries as a batch and avoids unnecessary execution cost. At last, we implement and experimentally evaluate our approaches.

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“…Hurtado et al in [15] propose two kinds of relaxation for triple pattern which exploit RDF entailment to relax the queries.…”

Section: Query Relaxation Modelmentioning

confidence: 99%

Section: Ranking Modelmentioning

confidence: 99%

Approximating query answering on RDF databases

2011

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“…Extensions are of two kinds : (i) the deep-similar function permits a relaxed comparison in term of structure between the query tree and the data tree; (ii) the close and similar predicates extend the equality comparison to a similarity comparison between the content of a node and a given value expressed in the query. [10] proposes an extension of the SPARQL Optional clause (called Relax). This clause permits to compute a set of generalizations of the RDF triplets involved in the SPARQL query using especially declarations done in the RDF Schema.…”

Section: Related Workmentioning

confidence: 99%

Flexible SPARQL Querying of Web Data Tables Driven by an Ontology

Buche

Dibie-Barthelemy

Chebil

2009

Flexible Query Answering Systems

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Abstract. This paper concerns the design of a workflow which permits to feed and query a data warehouse opened on the Web, driven by a domain ontology. This data warehouse has been built to enrich local data sources and is composed of data tables extracted from Web documents. We recall the main steps of our semi-automatic method to annotate Web data tables driven by a domain ontology. The output of this method is an XML/RDF data warehouse composed of XML documents representing Web data tables with their fuzzy RDF annotations. We then present how to query simultaneously the local data sources and the XML/RDF data warehouse, using the domain ontology, through a flexible querying language. This language allows preferences to be expressed in selection criteria using fuzzy sets. We study more precisely how to retrieve approximate answers extracted from the Web data tables by comparing preferences expressed as fuzzy sets with fuzzy annotations using SPARQL.

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“…From the perspective of query refinement [12] [20], the gap between users' information needs and its semantic querying is quantified by measuring several types of query ambiguities through incremental interaction. Graphical based search [21] also contributes a way, by building graph queries through browsing and selection on ontology.…”

Section: Related Workmentioning

confidence: 99%

SPARK: Adapting Keyword Query to Semantic Search

Zhou

Wang

Xiong

et al. 2007

Lecture Notes in Computer Science

127

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Abstract. Semantic search promises to provide more accurate result than present-day keyword search. However, progress with semantic search has been delayed due to the complexity of its query languages. In this paper, we explore a novel approach of adapting keywords to querying the semantic web: the approach automatically translates keyword queries into formal logic queries so that end users can use familiar keywords to perform semantic search. A prototype system named 'SPARK' has been implemented in light of this approach. Given a keyword query, SPARK outputs a ranked list of SPARQL queries as the translation result. The translation in SPARK consists of three major steps: term mapping, query graph construction and query ranking. Specifically, a probabilistic query ranking model is proposed to select the most likely SPARQL query. In the experiment, SPARK achieved an encouraging translation result.

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A Relaxed Approach to RDF Querying

Cited by 25 publications

References 9 publications

Approximating query answering on RDF databases

Approximating query answering on RDF databases

Flexible SPARQL Querying of Web Data Tables Driven by an Ontology

SPARK: Adapting Keyword Query to Semantic Search

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