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modelassistant-replication-package

https://github.com/claudiodsi/modelassistant-replication-package

Science Score: 44.0%

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    Low similarity (12.5%) to scientific vocabulary
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Repository

Basic Info
  • Host: GitHub
  • Owner: claudioDsi
  • Language: Python
  • Default Branch: main
  • Size: 3.7 MB
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  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Readme Citation

README.md

ModelAssistant-Replication-Package

Overview

This repository contains the replication package for the article entitled "Using graph-based structures in intelligent modeling assistants: an experience report"

Features

  • The repo is structured as follows.
  • The folder MORGAN contains the source code of the tool used in the paper
  • For the BORA tool please refer to the corresponding repository available here
  • The dataset used in the evaluation are stored in the Dataset.zip folder

Installation

To run MORGAN please follows the following steps:

  1. Clone the repository: bash git clone https://github.com/claudioDsi/ModelAssistant-Replication-Package.git
  2. Navigate to the project directory: bash cd ModelAssistant-Replication-Package
  3. Install the dependencies from the requirement.txt file: bash pip install -r /path/to/requirements.txt

Please note that Python 3.7 is required for the Grakel library.

Usage

To run MORGAN, you need to run the following steps:

bash python main.py data_path n_classes n_items size rec_type where:

  • data_path: (string) Path to the dataset folder containing the train and test files.
  • n_classes: (integer) Number of classes for recommendation.
  • n_items: (integer) Number of items to process for each recommendation.
  • size: (integer) Size of the test according to different configurations
  • rec_type: (string) Type of recommendation (class or attrs)

To compute the similarity metrics, you can use the compute_similarity function in the main.py by specifying the source data, i.e., one of the three dataset contained in teh zip file, and the output CSV name.

Owner

  • Login: claudioDsi
  • Kind: user
  • Company: University of L'Aquila

Claudio Di Sipio

Citation (CITATION.cff) 

cff-version: 1.2.0
authors:
  - family-names: Ibrahimi
    given-names: Lirian
    affiliation: Johannes Kepler University Linz
  - family-names: Di Sipio
    given-names: Claudio
    affiliation: University of L'Aquila
  - family-names: Di Ruscio
    given-names: Davide
    affiliation: University of L'Aquila
  - family-names: Wimmer
    given-names: Manuel
    affiliation: Johannes Kepler University Linz
title: "Using graph-based structures in intelligent modeling assistants: an
experience report - Replication Package"
version: 2.0.4
date-released: 2024-30-10

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Dependencies

requirements.txt pypi