Abstract
Graph theory and the study of networks can be traced back to Leonhard Euler’s original paper on the Seven Bridges of Konigsberg, in 1736 [1]. Although the mathematical foundations to understanding graphs have been laid out over the last few centuries [2–4], it wasn’t until recently, with the advent of modern computers, that parsing and analysis of large-scale graphs became tractable [5]. In the last decade, graph theory gained mainstream popularity following the adoption of graph models for new applications domains, including social networks and the web of data, both generating extremely large and dynamic graphs that cannot be adequately handled by legacy graph management applications [6].
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Notes
- 1.
Extract Transform and Load; a generic term in the data industry for data manipulation that occurs prior to the exercise of real interest.
- 2.
Examples of ‘problem’ are minimal closure, shortest path, subgraph-matching, graph-isomorphism, etc.
- 3.
Based upon a very early prototype of a small sub-set of the proposed KEL language.
- 4.
In PIG you do not need to provide data types or even declare the schema for data although the PIG manual warns “it may not work very well if you don’t”.
- 5.
The man that created BCPL which eventually led to C; and a great ‘Compiler Theory’ lecturer too!.
- 6.
In fact some of the elements and benefits of both appear within KEL. However, at all points we believe that the thought process of the encoder should be paramount rather than the academic purity of a particular abstraction.
- 7.
The PARSE format allows entities and facts which have been extracted from text files to appear within the knowledge base.
- 8.
Here the UID does not exist and so is generated based upon those fields
- 9.
Here the UID is existing and called UID in the underlying data
- 10.
Once an entity with a UID has been declared then the type can be used to implicitly declare a foreign key existing within another part of the data.
- 11.
Called allows for both bi-directional and unidirectional links to be used in text
- 12.
There is a separate category of graph function which returns scalar results; these are covered by the syntax discussed already.
- 13.
At the moment it is envisaged that the outputs of an algorithm are only recorded in the algorithm declaration and implicitly appear as #1, #2 etc. in the production. This may prove too sloppy if algorithms with many, many outputs are invented.
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Bayliss, D., Villanustre, F. (2016). Graph Processing with Massive Datasets: A Kel Primer. In: Big Data Technologies and Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-44550-2_11
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