Azerbaijan Text Clustering using Machine Learning Methods
| dc.contributor.author | Bashirov, Sokrat | |
| dc.date.accessioned | 2025-11-04T06:52:07Z | |
| dc.date.available | 2025-11-04T06:52:07Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | In this digital era, the explosion of textual data is causing us to develop sophisticated text mining and clustering methods. Although the state of art has improved for most well-resourced languages, relatively little research had been carried out on a language with smaller resource like Azerbaijani. In this thesis I investigated using clustering algorithms to enhance the information and communication access in Azerbaijani speaking community. 15,500 news articles were used compiled as a part of oxu.az. So, K-means, Fuzzy-Kmeans, Agglomerative Hierarchical Clustering, Spectral Clustering along with Gaussian Mixture Model (GMM) and Latent Dirichlet Allocation were deployed. They were evaluated on the basis of Silhouette Score (SS) and Davies-Bouldin Index. Word2Vec embeddings yield higher ARI than TF-IDF, while Spectral Clustering and LDA report superior scores owing to their capability of mapping complex workout nodes. The future works will improve the Pre-processing, hybrid Clustering and Deep Learning Embeddings. Applications to real-world problems ranging from recommendation systems and content categorization, all of which will build experience with the models. | en_US |
| dc.identifier.uri | http://hdl.handle.net/20.500.12181/1525 | |
| dc.language.iso | en | en_US |
| dc.publisher | ADA University | en_US |
| dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
| dc.subject | Text mining -- Azerbaijan. | en_US |
| dc.subject | Natural language processing (Computer science) -- Azerbaijan. | en_US |
| dc.subject | Machine learning -- Azerbaijan. | en_US |
| dc.subject | Data mining -- Azerbaijan. | en_US |
| dc.title | Azerbaijan Text Clustering using Machine Learning Methods | en_US |
| dc.type | Thesis | en_US |
| dcterms.accessRights | Absolute Embargo Only Bibliogrsphic Record and Abstract |