تحليل احالة الضمائر

المؤلفون
فائز موسى لهمود الرفيعي, سلمى عبدالباقي محمود
تاريخ النشر 2014
مجلة مجلة واسط للعلوم والطب
المجلد 7
الإصدار 2
الناشر جامعة واسط

Arabic words clustering by using K-means algorithm

المؤلفون
Dhyaa Shaheed Al-Azzawy, Faiez Musa Lahmood Al-Rufaye
تاريخ النشر 2017/3/7
المؤتمر
2017 Annual Conference on New Trends in Information & Communications Technology Applications (NTICT)
الصفحات 263-267
الناشر IEEE
الوصف
These We mean by the clustering is a technique to divide the text into clusters of words, so that words in the same cluster are similar to each other. As humans we can have significant difficulty understanding the clustering of words to each other. To a machine, it represents a huge challenge. To address this problem, this paper describes a new words-clustering technique based on certain text characteristics; by building a system to cluster words in the text depending on characteristics such as morphological, syntactic and Semantic. The clustering is a method of Unsupervised Machine Learning methods, where it collects words with other have similar characteristics in the clusters based on Similarity Function to calculate the distance between those words. We depended on k-mean Clustering to calculate the distance between words, then generating clusters for all referred words in the text. Finally, we will evaluate our …

Arabic text mining based on clustering and coreference resolution

المؤلفون
Salma Mahmood, Faiez Musa Lahmood Al-Rufaye
تاريخ النشر
2017/4/26
المؤتمر
2017 International Conference on Current Research in Computer Science and Information Technology (ICCIT)
الصفحات
140-144
الناشر
IEEE
الوصف
Text mining discover and extract useful information from documents, whenever increase the size and number documents leads to redouble features. The huge features for the documents adds challenge to text mining called high dimension. The aim of this proposed study is minimize the high dimension of the documents, and improve Arabic text mining using clustering. In order to achieve this goal, we propose to applied coreference resolution technique using the clustering algorithms k-mediods and k-means. This study uses the similarity metrics Euclidean and Cosine. The system implements using a corpus contains on 200 sport news Arabic. Finally, evaluation measures are used including (Precision' Recall and F-measure) to evaluate our system.

Mammogram image segmentation for improving the diagnosis of dense breast issues

المؤلفون
Raad Farhood Chisab Marwah Thamer Ali, Faiez Musa Lahmood
تاريخ النشر
2019
مجلة
8
المجلد
1
الإصدار
2019
الصفحات
44-52
الناشر
Science Publishing CorporationPublisher of International Academic Journals