Summary of Multisiam: a Multiple Input Siamese Network For Social Media Text Classification and Duplicate Text Detection, by Sudhanshu Bhoi et al.
MultiSiam: A Multiple Input Siamese Network For Social Media Text Classification And Duplicate Text Detection
by Sudhanshu Bhoi, Swapnil Markhedkar, Shruti Phadke, Prashant Agrawal
First submitted to arxiv on: 6 Jan 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG); Social and Information Networks (cs.SI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel approach to organizing social media content is presented, addressing the issue of similar posts making it difficult to access desired information. A multiple-input Siamese neural network, called MultiSiam, is proposed, which can group and categorize duplicate posts across different social media accounts. This model is then used in conjunction with a Social Media Classification and Duplication Model (SMCD) for both text duplication detection and grouping. The applicability of the MultiSiam network in various applications is also demonstrated. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Social media is making it harder to find what you’re looking for, because lots of posts look similar! To fix this, researchers came up with a new way to group and categorize duplicate posts from different social media accounts. They created a special kind of computer program called MultiSiam that can do this job well. This program can also be used in other situations by just changing its settings. The goal is to make it easier for people to find the information they want on social media. |
Keywords
* Artificial intelligence * Classification * Neural network
