RDF data distributed parallel semantic coding method

A technology of parallel semantics and encoding methods, applied in the field of semantic web, can solve problems such as insufficient efficiency of distributed compression algorithms, inability to meet massive data requirements, unfavorable distributed query or reasoning, etc.

Active Publication Date: 2016-09-07
FUZHOU UNIV
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AI Technical Summary

Problems solved by technology

[0004] The centralized environment cannot meet the needs of massive data, while the compressed coding in the distributed environment does not represent any semantic information, which is not conducive to distributed query or reasoning
Some distributed compression algorithms are not efficient enough in the data inversion phase

Method used

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  • RDF data distributed parallel semantic coding method
  • RDF data distributed parallel semantic coding method
  • RDF data distributed parallel semantic coding method

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Embodiment Construction

[0046] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0047] This embodiment provides a distributed parallel semantic coding method for RDF data (Semantic Coding with Ontology on MapReduce, SCOM for short). According to the characteristics of MapReduce combined with ontology to build class relationship and attribute relationship model, according to the model to classify and encode RDF data, so as to realize the distributed parallel compression coding of RDF data, in which the SCOM scheme is divided into compression coding stage and inversion stage, such as figure 1 As shown, it specifically includes the following steps:

[0048] Step S1: read in the RDF ontology file, construct a class relationship model and an attribute relationship model, and generate a mapping file of classes and their encodings and a mapping file of attributes and their encodings;

[0049] Step S2: Read in the RDF data file, split the...

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Abstract

The invention relates to an RDF data distributed parallel semantic coding method. The method specifically comprises the following steps of S1: reading an RDF ontology file and constructing a class relation model and an attribute relation model; S2: reading an RDF data file, dividing a triple into triple items, classifying the triple items by class, deleting the repeated triple items, and generating prefix codes; filtering the triple items to ensure the consistency of RDF triple codes and enable the same triple item not to be allocated with different codes; S3: coding the triple items to generate a dictionary table; S4: coding the triple to generate a coded triple file; and S5: taking a result file in the step S4 as an input of the step S5, and performing inversion according to the dictionary table in the step S3 to generate an original RDF data file. According to the method, compressed coding and inversion of large-scale data can be efficiently realized in combination with ontology in a distributed environment.

Description

technical field [0001] The invention relates to the technical field of semantic web, in particular to a distributed parallel semantic encoding method for RDF data. Background technique [0002] Due to the large-scale nature of RDF data, its management has limitations. In order to speed up the query or reasoning of RDF data and reduce the storage space of the data, the common practice is to compress and encode the triples. Compression coding has been proven to be an effective coding, by replacing the original triplet item (subject or predicate or object) with a numerical value (ID), and finally converts all triplet data into numerical data. Centralized environments are not suitable for encoding large-scale data due to memory constraints. Research on RDF data distributed parallel compression coding algorithm is a relatively new field at present. Goodman et al. proposed a method to adapt to linear detection on the Gray XMT machine, and realized parallel encoding on a single d...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06F17/27
CPCG06F16/24564G06F16/2471G06F40/30
Inventor 汪璟玢郑翠春
Owner FUZHOU UNIV
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