Topic Model Implementation To Find Related Documents In Corporate Archives In Real Life: “A Case Scenario On Knowledge Retrieval”
| dc.contributor.author | Medeni, İhsan Tolga | |
| dc.contributor.author | Medeni, Tunç Durmuş | |
| dc.contributor.authorID | 181215 | tr_TR |
| dc.date.accessioned | 2024-05-14T08:03:26Z | |
| dc.date.available | 2024-05-14T08:03:26Z | |
| dc.date.issued | 2013 | |
| dc.department | Çankaya Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü | en_US |
| dc.description.abstract | Today’s organizations were mostly built over their documents. These documents are very crucial sources of knowledge. Even they know the existence of these documents, most of the time, it is nearly impossible to extract captive knowledge inside. In these conditions, organizations choose re-prepare same document again rather than finding proper documents in the archives. On the other hand, finding these documents would save precious time and decrease redundancy of the work. Topic model idea basically focuses on extraction of knowledge from these types of documents. In this study, our aim is to give a summary of Topic Model research and try to explain latest model concept over an imaginary case scenario | en_US |
| dc.description.publishedMonth | 6 | |
| dc.identifier.citation | Medeni, İhsan Tolga; Medeni, Tunç Durmuş (2013). "Topic Model Implementation To Find Related Documents In Corporate Archives In Real Life: “A Case Scenario On Knowledge Retrieval”", International Journal of eBusiness and eGovernment Studies, Vol.5, No.1, pp.98-107. | en_US |
| dc.identifier.endpage | 107 | en_US |
| dc.identifier.issn | 2146-0744 | |
| dc.identifier.issue | 1 | en_US |
| dc.identifier.startpage | 98 | en_US |
| dc.identifier.uri | http://hdl.handle.net/20.500.12416/8291 | |
| dc.identifier.volume | 5 | en_US |
| dc.language.iso | en | en_US |
| dc.relation.ispartof | International Journal of eBusiness and eGovernment Studies | en_US |
| dc.rights | info:eu-repo/semantics/openAccess | en_US |
| dc.subject | Topic Model | en_US |
| dc.subject | Knowledge Extraction | en_US |
| dc.subject | Latent Semantic Analysis (LSA) | en_US |
| dc.subject | Probabilistic Latent Semantic Analysis (pLSA) | en_US |
| dc.subject | Latent Dirichlet Allocation (LDA) | en_US |
| dc.title | Topic Model Implementation To Find Related Documents In Corporate Archives In Real Life: “A Case Scenario On Knowledge Retrieval” | tr_TR |
| dc.title | Topic Model Implementation To Find Related Documents In Corporate Archives In Real Life: “A Case Scenario On Knowledge Retrieval” | en_US |
| dc.type | Article | en_US |
| dspace.entity.type | Publication |