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Technical component

SciNeM

Data Science Tool for Heterogeneous Network Mining

SciNeM is data science tool for metapath-based querying and analysis of Heterogeneous Information Networks. It enables entity ranking, similarity searches, and community detection.

SciNeM is a data science tool for metapath-based querying and analysis of Heterogeneous Information Networks (HINs). It currently supports the following operations, given a user-specified metapath:

  • ranking entities using a random walk mode,
  • retrieving the most similar pairs of entities,
  • finding the most similar entities to a query entity, and
  • discovering entity communities via several community detection algorithms.

All supported operations have been implemented in a scalable manner, utilising Apache Spark for scaling out through parallel and distributed computation. SciNeM has a modular architecture making it easy to extend it with additional algorithms and functionalities. Moreover, it provides an intuitive, Web-based user interface to build and execute complex constrained metapath-based queries and to explore and visualise the corresponding results.

URL: http://scinem.imsi.athenarc.gr/

Publications: https://doi.org/10.5441/002/edbt.2021.76

Functionalities

Ranking

Assigns centrality scores to entities in a graph using a random walk mode.

Similarity search

Identifies most similar entities to a given entity.

Community detection

Discovers communities of entities in the graph.

Roadmap

Coming soon

For

Research Communities
Research Managers
Research Organisations
Innovators
Funders & Policy Makers

Provided by

Contacts

Serafeim Chatzopoulos
Thanasis Vergoulis