Top-k Exploration of Query Candidates for Efficient Keyword Search on Graph-Shaped (RDF) Data

Since SPARQL has been the standard language for querying RDF data, keyword search based on keywords-to-SPARQL translation attracts more intention. However, existing keyword search based on keywords-to-SPARQL translation have limitations that the schema used for keyword-to-SPARQL translation is incomplete so that wrong or incomplete answers are returned and advantages of indexes are not fully taken. To address the issues, an inter-entity relationship summary (ER-summary) is constructed by distilling all the inter-entity relationships of RDF data graph. On ER-summary, we draw circles around each vertex with a given radius r and in the circles we build the shortest property path index (SP-index), the shortest distance index (SD-index) and the r-neighborhoods index by using dynamic programming algorithm. Rather than searching for top-k subgraphs connecting all the keywords centered directly as most existing methods do, we use these indexes to translate keyword queries into SPARQL queries to realize exchanging space for time. Extensive experiments show that our approach is efficient and effective.

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Scalable Keyword Search on Large RDF Data

IEEE Transactions on Knowledge and Data Engineering ◽

10.1109/tkde.2014.2302294 ◽

2014 ◽

Vol 26 (11) ◽

pp. 2774-2788 ◽

Cited By ~ 40

Author(s):

Wangchao Le ◽

Feifei Li ◽

Anastasios Kementsietsidis ◽

Songyun Duan

Keyword(s):

Keyword Search ◽

Rdf Data

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Pattern-Based Keyword Search on RDF Data

The Semantic Web - Lecture Notes in Computer Science ◽

10.1007/978-3-319-47602-5_7 ◽

2016 ◽

pp. 30-34 ◽

Cited By ~ 2

Author(s):

Hanane Ouksili ◽

Zoubida Kedad ◽

Stéphane Lopes ◽

Sylvaine Nugier

Keyword(s):

Keyword Search ◽

Rdf Data

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RDF Keyword Search by Query Computation

Journal of Database Management ◽

10.4018/jdm.2018100101 ◽

2018 ◽

Vol 29 (4) ◽

pp. 1-27 ◽

Cited By ~ 1

Author(s):

Zongmin Ma ◽

Xiaoqing Lin ◽

Li Yan ◽

Zhen Zhao

Keyword(s):

Keyword Search ◽

Priority List ◽

Graph Expansion ◽

Path Index ◽

Degree Of A Vertex ◽

Rdf Data ◽

Summary Graph ◽

Entity Relationship ◽

Keyword Searches ◽

Prioritization Scheme

Keyword searches based on the keywords-to-SPARQL translation is attracting more attention because of a growing number of excellent SPARQL search engines. Current approaches for keyword search based on the keywords-to-SPARQL translation suffer from returning incomplete answers or wrong answers due to a lack of underlying schema information. To overcome these difficulties, in this article, we propose a new keyword search paradigm by translating keyword queries into SPARQL queries for exploring RDF data. An inter-entity relationship summary with complete schema information is distilled from the RDF data graph for composing SPARQL queries. To avoid potentially wasteful summary graph expansion, we develop a new search prioritization scheme by combining the degree of a vertex with the distance from the original keyword element. Starting from the ordered priority list that is built in advance, we apply the forward path index to faster find the top-k subgraphs, which are relevant to the conjunction of the entering keywords. The experimental results show that our approach is efficient and scalable.

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Diversified spatial keyword search on RDF data

The VLDB Journal ◽

10.1007/s00778-020-00610-z ◽

2020 ◽

Vol 29 (5) ◽

pp. 1171-1189

Author(s):

Zhi Cai ◽

Georgios Kalamatianos ◽

Georgios J. Fakas ◽

Nikos Mamoulis ◽

Dimitris Papadias

Keyword(s):

Keyword Search ◽

Spatial Keyword Search ◽

Rdf Data

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