An incremental approach for solution of text clustering problem

Makaleler > Tam Makale · 2019

Yazarlar: Burak ORDİN, Duygu Selin TURAN, Nur Uylaş Satı

International Journal of Knowledge Engineering and Data Mining, Diğer Kurumların Hakemli Dergileri, Uluslararası, 2019, cilt 6, ss 273-288

DOI: 10.1504/ijkedm.2019.102488

Özet

<p><span style="color: rgb(33, 37, 41); font-family: -apple-system, BlinkMacSystemFont, &quot;Segoe UI&quot;, Roboto, &quot;Helvetica Neue&quot;, Arial, &quot;Noto Sans&quot;, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;, &quot;Segoe UI Symbol&quot;, &quot;Noto Color Emoji&quot;; font-size: 14px;">Text clustering is a significant study field in data mining. In text clustering, hidden-information is revealed by analysing text datasets with data mining techniques. Text clustering is used in many current application areas such as document recognition, document organisation, indexing, and visualisation. Since it is used in important applications it is in need of efficient algorithms. In this paper,&nbsp;</span><i style="color: rgb(33, 37, 41); font-family: -apple-system, BlinkMacSystemFont, &quot;Segoe UI&quot;, Roboto, &quot;Helvetica Neue&quot;, Arial, &quot;Noto Sans&quot;, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;, &quot;Segoe UI Symbol&quot;, &quot;Noto Color Emoji&quot;; font-size: 14px;">k</i><span style="color: rgb(33, 37, 41); font-family: -apple-system, BlinkMacSystemFont, &quot;Segoe UI&quot;, Roboto, &quot;Helvetica Neue&quot;, Arial, &quot;Noto Sans&quot;, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;, &quot;Segoe UI Symbol&quot;, &quot;Noto Color Emoji&quot;; font-size: 14px;">-means based algorithms in literature are investigated and a novel&nbsp;</span><i style="color: rgb(33, 37, 41); font-family: -apple-system, BlinkMacSystemFont, &quot;Segoe UI&quot;, Roboto, &quot;Helvetica Neue&quot;, Arial, &quot;Noto Sans&quot;, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;, &quot;Segoe UI Symbol&quot;, &quot;Noto Color Emoji&quot;; font-size: 14px;">k</i><span style="color: rgb(33, 37, 41); font-family: -apple-system, BlinkMacSystemFont, &quot;Segoe UI&quot;, Roboto, &quot;Helvetica Neue&quot;, Arial, &quot;Noto Sans&quot;, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;, &quot;Segoe UI Symbol&quot;, &quot;Noto Color Emoji&quot;; font-size: 14px;">-means based text clustering algorithm is defined. Proposed algorithm is compared with existing&nbsp;</span><i style="color: rgb(33, 37, 41); font-family: -apple-system, BlinkMacSystemFont, &quot;Segoe UI&quot;, Roboto, &quot;Helvetica Neue&quot;, Arial, &quot;Noto Sans&quot;, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;, &quot;Segoe UI Symbol&quot;, &quot;Noto Color Emoji&quot;; font-size: 14px;">k</i><span style="color: rgb(33, 37, 41); font-family: -apple-system, BlinkMacSystemFont, &quot;Segoe UI&quot;, Roboto, &quot;Helvetica Neue&quot;, Arial, &quot;Noto Sans&quot;, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;, &quot;Segoe UI Symbol&quot;, &quot;Noto Color Emoji&quot;; font-size: 14px;">-means algorithm in literature on five real-world datasets. Obtained implications show that recommended algorithm is efficient and useful.</span><br></p>

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