MultiSiam: A Multiple Input Siamese Network For Social Media Text Classification And Duplicate Text Detection
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866916089910263808 |
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| author | Bhoi, Sudhanshu Markhedkar, Swapnil Phadke, Shruti Agrawal, Prashant |
| author_facet | Bhoi, Sudhanshu Markhedkar, Swapnil Phadke, Shruti Agrawal, Prashant |
| contents | Social media accounts post increasingly similar content, creating a chaotic experience across platforms, which makes accessing desired information difficult. These posts can be organized by categorizing and grouping duplicates across social handles and accounts. There can be more than one duplicate of a post, however, a conventional Siamese neural network only considers a pair of inputs for duplicate text detection. In this paper, we first propose a multiple-input Siamese network, MultiSiam. This condensed network is then used to propose another model, SMCD (Social Media Classification and Duplication Model) to perform both duplicate text grouping and categorization. The MultiSiam network, just like the Siamese, can be used in multiple applications by changing the sub-network appropriately. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_06783 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | MultiSiam: A Multiple Input Siamese Network For Social Media Text Classification And Duplicate Text Detection Bhoi, Sudhanshu Markhedkar, Swapnil Phadke, Shruti Agrawal, Prashant Computation and Language Artificial Intelligence Machine Learning Social and Information Networks Social media accounts post increasingly similar content, creating a chaotic experience across platforms, which makes accessing desired information difficult. These posts can be organized by categorizing and grouping duplicates across social handles and accounts. There can be more than one duplicate of a post, however, a conventional Siamese neural network only considers a pair of inputs for duplicate text detection. In this paper, we first propose a multiple-input Siamese network, MultiSiam. This condensed network is then used to propose another model, SMCD (Social Media Classification and Duplication Model) to perform both duplicate text grouping and categorization. The MultiSiam network, just like the Siamese, can be used in multiple applications by changing the sub-network appropriately. |
| title | MultiSiam: A Multiple Input Siamese Network For Social Media Text Classification And Duplicate Text Detection |
| topic | Computation and Language Artificial Intelligence Machine Learning Social and Information Networks |
| url | https://arxiv.org/abs/2401.06783 |