Özet. Yazılım teknolojileri hızla ilerlemekte ve buna paralel olarak hem kamu alanında hem de özel sektörde gerçekleştirilen yazılım projelerinin sayısı artmaktadır. Yazılım otomasyon projelerinden elde edilen en büyük çıktılardan birisi kuşkusuz ki üretilen verilerdir. Yüksek boyutlu, anlaşılması güç bu verilerin işlenerek, daha anlamlı ve yönlendirici verilere dönüştürülmesi önemli bir ihtiya...

In this paper, we describe our work at subtopic mining subtask in NTCIR-9 in simplified Chinese. To find possible subtopics of a specific query, we select related queries recorded by query log, or titles of searching results provided by Google and Baidu, or the catalog of corresponding entry in Baidu encyclopedia, which are lexically similar as the original query, then we apply k-means algorith...

هدف: پژوهش حاضر با هدف تحلیل و بررسی پیامدهای شبکه‌سازی سیاسی در نظام سیاست‌گذاری سازمان‌های دولتی استان لرستان انجام پذیرفت.طراحی/ روش‌­شناسی/ رویکرد : دارای رویکردی آمیخته است که از نظر هدف، کاربردی حیث ماهیت روش، توصیفی پیمایشی است. مشارکت‌کنندگان را مدیران تشکیل می­‌دهند استفاده اصل کفایت نظری روش نمونه­‌گیری هدفمند 16 نفر آنان به عنوان اعضای نمونه انتخاب شدند. بخش کیفی برای گردآوری داده مص...

The intelligent LINEX k-means clustering is a generalization of the k-means clustering so that the number of clusters and their related centroid can be determined while the LINEX loss function is considered as the dissimilarity measure. Therefore, the selection of the centers in each cluster is not randomly. Choosing the LINEX dissimilarity measure helps the researcher to overestimate or undere...

identifying clusters or clustering is an important aspect of data analysis. it is the task of grouping a set of objects in such a way those objects in the same group/cluster are more similar in some sense or another. it is a main task of exploratory data mining, and a common technique for statistical data analysis this paper proposed an improved version of k-means algorithm, namely persistent k...

Due to the progressive growth of the amount of data available in a wide variety of scientific fields, it has become more difficult to manipulate and analyze such information. Even though datasets have grown in size, the K-means algorithm remains as one of the most popular clustering methods, in spite of its dependency on the initial settings and high computational cost, especially in terms of d...