Machine learning approach for text and document mining
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Abstract (arXiv)
Text Categorization (TC), also known as Text Classification, is the task of automatically classifying a set of text documents into different categories from a predefined set. If a document belongs to exactly one of the categories, it is a single-label classification task; otherwise, it is a multi-label classification task. TC uses several tools from Information Retrieval (IR) and Machine Learning (ML) and has received much attention in the last years from both researchers in the academia and industry developers. In this paper, we first categorize the documents using KNN based machine learning approach and then return the most relevant documents.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Jun 2014.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 0; 2024: 1; 2025: 1.
6 papers.
- 2022KNN-Diffusion: Image Generation via Large-Scale Retrievalcited by 135
- 2024Better RAG using Relevant Information Gaincited by 7
- 2025Scalable Disk-Based Approximate Nearest Neighbor Search with Page-Aligned Graphcited by 2
- 2021Classification of Anuran Frog Species Using Machine Learningcited by 1
- 2021Automatic Monitoring Social Dynamics During Big Incidences: A Case Study of COVID-19 in Bangladeshcited by 0
- 2022A New Dataset for Topic-Based Paragraph Classification in Genocide-Related Court Transcriptscited by 0
- 2025Scalable Disk-Based Approximate Nearest Neighbor Search with Page-Aligned Graph29 Sep 2025
- 2024Better RAG using Relevant Information Gain16 Jul 2024
- 2022KNN-Diffusion: Image Generation via Large-Scale Retrieval6 Apr 2022
- 2022A New Dataset for Topic-Based Paragraph Classification in Genocide-Related Court Transcripts6 Apr 2022
- 2021Classification of Anuran Frog Species Using Machine Learning9 Dec 2021
- 2021Automatic Monitoring Social Dynamics During Big Incidences: A Case Study of COVID-19 in Bangladesh24 Jan 2021