[NEW FEATURE]Improve duplicate algorithm

[lduf]

Find new algorithms to improve our duplicate detection. You can use ChatGPT to find some new ideas. Once done => Implement the solution within the Laravel project.

I think the best way to do :

• Create a parent classed named for eg MatchingAlgorithm
• Create a child class for each algo

=> this way you ll have the same architecture and the same function.

You ll also need to adapt the Duplicate model to call the newly created MatchingAlgorithm

[github-actions[bot]]

AI-Assisted Response:

Issue Summary: Enhancing Duplicate Detection with New Algorithms

The issue focuses on improving the duplicate detection system in a Laravel project by finding and integrating new algorithms. The proposal includes using resources like ChatGPT to brainstorm innovative algorithmic ideas. After identifying suitable algorithms, the next step is to implement those within the Laravel framework.

The suggested implementation strategy is to organize the codebase using object-oriented design principles:

1. Create an abstract base class named MatchingAlgorithm.
2. Derive a child class for each specific algorithm from this parent class.

This structure will provide consistency across different algorithms and facilitate straightforward integration with the system. The issue also mentions the need to update the Duplicate model in order to utilize the new MatchingAlgorithm base class.

Issue Categorization

This issue is classified as a feature request since it calls for new functionality—improved duplicate detection algorithms—to be added to the existing software.

Questions for Clarification

1. @lduf, could you please provide more context on the current duplicate detection system? What algorithms are in use, and what are their limitations?
2. Have you already identified specific algorithms that you would like to explore, or are you looking for suggestions from scratch?
3. What criteria will you use to evaluate the new algorithms' effectiveness in duplicate detection?
4. Is there a specific workflow or data structure the Duplicate model uses that the new algorithms should be compatible with?
5. Could you clarify if there is an expected performance benchmark for the new algorithms compared to the current system?
6. Is there a timeline for when you plan to have the new algorithms researched and potentially implemented?

[github-actions[bot]]

AI-Assisted Response:

Issue Summary: Enhancement of Duplicate Detection with New Algorithms

The issue suggests that there is potential for improving the system's ability to detect duplicates by introducing new algorithms. The user recommends utilizing ChatGPT for generating innovative ideas for such algorithms. Once identified, the proposed solution should be integrated into an existing Laravel project.

The user outlines a potential implementation strategy involving object-oriented programming:

• A base parent class, possibly named MatchingAlgorithm, should be created.
• Specific algorithms would be represented as child classes inheriting from this parent class, ensuring consistent architecture and method interfaces.
• The existing Duplicate model should be modified to utilize the new MatchingAlgorithm class structure.

Issue Categorization:

This is a feature request, as it proposes the addition of new functionality to improve an already present system within the project.

Questions for Clarification:

• @lduf, could you specify the criteria for duplicate detection that our current system uses and highlight which aspects need improvement?
• Are there specific types of algorithms you have in mind for this issue, or are you open to any that show promise after researching with ChatGPT?
• Do you require the new algorithms to be created from scratch, or can they be adaptations of existing open-source solutions?
• Is there a performance benchmark or a target that the new algorithms should meet or exceed?
• Could you elaborate on how you envision the interaction between Duplicate model and the MatchingAlgorithm classes? Will there be a need for a strategy pattern to switch algorithms at runtime or is this a static implementation?
• Are there any constraints or requirements for the new algorithms regarding their complexity, execution time, or resource usage?

[lduf]

A potential solution :

• Get the phonetic transcription for each name with Metaphone algorithm, already implemented in php
• Calculate the Levenshtein distance between each phonetic transcription

Other phonetic algorithms :

• Soundex
• Double Metaphone

Other algorithms to calculate distances :

• Jaro-Winkler (similar to Levenshtein, but takes in consideration the number of common letters in the prefix of two names)
• N-gram : compares each group of letters in a name, and not just every single letter

[create-issue-branch[bot]]

Branch feature/issue-466-_NEW_FEATURE_Improve_duplicate_algorithm created!