symbolic-kg
This repository contains code of my on going PhD research.
Science Score: 57.0%
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Repository
This repository contains code of my on going PhD research.
Basic Info
- Host: GitHub
- Owner: Siraj1munir
- License: apache-2.0
- Language: Jupyter Notebook
- Default Branch: main
- Size: 137 KB
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- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
This repository contains the code base for the paper presented at SmartNets'23
Towards symbolic representation-based modeling of Temporal Knowledge Graphs
Symbolic representation helps us to represent information in a well-defined rule-driven fashion. Currently, there are several ways to represent Knowledge Graphs in general. However, in this work, we extended the implementation of symbolic representation to model domain-oriented temporal Knowledge Graphs. For symbolic representation, we incorporated Horn rules and SWRL (Semantic Web Rule Language). The presented approach is semi-autonomous: (i) we extracted hand-crafted rules and (ii) we utilized the PSyKE (Platform for Symbolic Knowledge Extraction) package to extract some rules automatically from raw data logs. For domain modeling, we targeted a smart industry environment. To validate the proposed model, we conducted a counterfactual study using Knowledge Graph and network analysis for fact-finding and filtering.
To Model KG with Neo4j
Define constraints over entities (ex: CREATE CONSTRAINT FOR (p:Person) REQUIRE p.name IS UNIQUE)
Import the dataset you desire using LOAD CSV (Refer to Neo4j Documentation for example).
Import or Define relationships and Query
Reference
@INPROCEEDINGS{10215541,
author={Munir, Siraj and Ferretti, Stefano},
booktitle={2023 International Conference on Smart Applications, Communications and Networking (SmartNets)},
title={Towards symbolic representation-based modeling of Temporal Knowledge Graphs},
year={2023},
volume={},
number={},
pages={1-8},
keywords={Semantic Web;Knowledge engineering;Industries;Analytical models;Filtering;Knowledge graphs;Network analyzers;Symbolic Representation;Temporal Knowledge Graph;Semantic Representation;Network Analysis},
doi={10.1109/SmartNets58706.2023.10215541}}
Owner
- Name: Siraj Munir
- Login: Siraj1munir
- Kind: user
- Location: Urbino, Italy
- Company: University of Urbino Carlo Bo
- Website: https://www.linkedin.com/in/siraj-munir-2b59a7b5
- Repositories: 2
- Profile: https://github.com/Siraj1munir
I'm Data Scientist passionate to work on Deep and machine learning techniques to inspire the world.
Citation (citation.cff)
If you like this work feel free to cite
@INPROCEEDINGS{10215541,
author={Munir, Siraj and Ferretti, Stefano},
booktitle={2023 International Conference on Smart Applications, Communications and Networking (SmartNets)},
title={Towards symbolic representation-based modeling of Temporal Knowledge Graphs},
year={2023},
volume={},
number={},
pages={1-8},
keywords={Semantic Web;Knowledge engineering;Industries;Analytical models;Filtering;Knowledge graphs;Network analyzers;Symbolic Representation;Temporal Knowledge Graph;Semantic Representation;Network Analysis},
doi={10.1109/SmartNets58706.2023.10215541}}
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