Information retrieval in big data using cognitive approaches
Fuente:
arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866918169044582400 |
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| author | Acharjee, Santanu Choudhury, Ripunjoy |
| author_facet | Acharjee, Santanu Choudhury, Ripunjoy |
| contents | Due to the exponential growth of big data in this digital era, an advanced method for effective information retrieval becomes essential. The basic objective of this paper is to propose a topology-based method for cognitive information retrieval (CIR) in big data environments. By using concepts such as cognitive similarity distances, metric spaces, retrieval topologies, etc., this paper aims to propose the semantic alignment between user queries and document repositories. The paper also extends this approach to incorporate logical connectives in cognitive information retrieval. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_20837 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Information retrieval in big data using cognitive approaches Acharjee, Santanu Choudhury, Ripunjoy General Mathematics 94A16, 68T09, 68P01, 68T27, 62R40, 30L15 Due to the exponential growth of big data in this digital era, an advanced method for effective information retrieval becomes essential. The basic objective of this paper is to propose a topology-based method for cognitive information retrieval (CIR) in big data environments. By using concepts such as cognitive similarity distances, metric spaces, retrieval topologies, etc., this paper aims to propose the semantic alignment between user queries and document repositories. The paper also extends this approach to incorporate logical connectives in cognitive information retrieval. |
| title | Information retrieval in big data using cognitive approaches |
| topic | General Mathematics 94A16, 68T09, 68P01, 68T27, 62R40, 30L15 |
| url | https://arxiv.org/abs/2510.20837 |