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Article
Approach for Spatial Database Mining

Authors: Prof. Dr. Ala’a H. AL-Hamami --- Assest Prof. Dr. Soukaena Hassan --- Dr. Mazin Sameer Al-Hakeem
Journal: Journal of Baghdad College of Economic sciences University مجلة كلية بغداد للعلوم الاقتصادية الجامعة ISSN: 2072778X Year: 2012 Issue: 31 Pages: 407-420
Publisher: Baghdad College of Economic Sciences كلية بغداد للعلوم الاقتصادية

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Abstract

Most of the previous spatial mining works are depend on strategy of organizing the huge spatial data in a suitable data structure and usually the data organized as R-Tree. The data mining algorithms then applied on each level of R-Tree. This method causes time consuming and takes huge storage area and leads to inadequate results. The proposed approach suggests the following strategy for efficient spatial mining. It collects all the spatial data and organizes it (according to normalization and generalization) to a flat data base. After that the following steps will be executed: build the proposed spatial database, apply mining algorithms on the proposed Structure of the spatial data to extract the association rules, clusters and classes. Finally analyzes the resulted patterns from the mining algorithms.


Article
Mining Tutors’ Interesting Areas to Develop Researched Papers Using A Proposed Educational Data Mining System
تنقیب اھتمامات التدریسیین لكتابة بحث باستخدام نظام مقترح يف تنقیب البیانات التعلیمي

Author: Reem Jafar Ismail
Journal: Engineering and Technology Journal مجلة الهندسة والتكنولوجيا ISSN: 16816900 24120758 Year: 2012 Volume: 30 Issue: 10 Pages: 1732-1748
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

Educational Data Mining (EDM) is the process of converting raw data fromeducational systems to useful information that can be used by educational softwaredevelopers, students, teachers, parents, and other educational researchers. One ofthe difficulties in the educational institutes that face the tutor is how to write apaper. This work aims to help the tutor to write a researched paper on specificsubject by finding another tutor who is also interested in the same subject. This is done by exploring the tutor database by usingthe proposed educational data mining system, the tutor database is arranged inmultidimensional form will include: tutor’s teaching subjects, tutor’s interestingareas, tutor’s published researches, tutor’s Msc. and Ph.D research subjects. Theproposed system implements SMC and Cosine similarity measures with newproposed representation of tutor’s database. A clustering K-Means techniques andassociated rule generation is implemented by using WEKA data mining tool. Theresults obtained from that work are very useful for tutor and they give a richanalysis for developing researched papers for different tutors.

یقصد بتنقیب البیانات التعلیمي ھ و عملی ة تحوی ل ك م البیان ات ف ي انظم ة التعل یم ال ى معلوم اتمفیدة یمكن استخدامھا من قبل مبرمجي البرامجیات التعلیمیة او الطلاب او التدریسیین او الوال دیناو اي شخص تعلیمي باحث. احدى الصعوبات التي تواجھ التدریس ي ف ي المؤسس ات التعلیمی ة ھ وایجاد موضوع لكتابة بحث م ن اج ل الترقی ة العلمی ة ف ي مج ال الت دریس ل ذا ف ان البح ث المقت رحیھدف الى مساعدة التدریسي لكتابة بحث في موضوع ما عن طریق ایجاد تدریسي اخ ر ل ھ اھتم امفي نفس الموضوع وسیتم ذلك من خلال التنقیب ف ي قاع دة البیان ات التابع ة ال ى التدریس یین والت يتحتوي عل ى معلوم ات تش مل: موض وعات ال درس الت ي ت م تدریس ھا م ن قب ل التدریس ي ،مج الاتالاھتمام ات البحثی ة للتدریس ي ،البح وث الت ي ت م نش رھا م ن قب ل التدریس ي وك ذلك موض وعاتالماجستیر والدكتوراه التابعة لھ. ان البحث المقترح استخدم صیغة جدیدة لتمثیل البیانات في قاع دةK-Means البیان ات وك ذلك اس تخدم مقیاس ین للتش ابھ. لق د ت م ترتی ب بیان ات التدریس یین ض من لنت ائج .WEKA data mining باس تخدام Associated rule generation و Clusteringالمستخلصة من ھذا البحث مفیدة جدا للتدریسیین وتعطي تحلیل مستفیض من اجل تط ویر البح وثالعلمیة للتدریسیین.


Article
Application of Decision Tree as a Data Mining Tool in a health care

Authors: Sabiha Fathil Jawad صبحة فتحي جواد --- ZAKI .S. TOWFIK زكي سعيد توفيق
Journal: Journal of Kufa for Mathematics and Computer مجلة الكوفة للرياضيات والحاسوب ISSN: 11712076 Year: 2012 Volume: 1 Issue: 5 Pages: 102-109
Publisher: University of Kufa جامعة الكوفة

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Abstract

Abstract: This work demonstrates the application of decision tree, as data mining tool, in the health care system. Data mining has the capability for classification, prediction, estimation, and pattern recognition by using health databases. Databases of health systems contain significant information for decision making. It could be properly revealed with the application of appropriate data mining techniques. Decision trees are employed for identifying valuable information in health databases. In this paper Decision tree as a data mining tools is used for predication the spread types of disease of hepatitis virus in reigns that high affect to people with different temperature and prevention of this disease by using rules that needed to predicate the diseases .


Article
Data Mining based Prediction of Medical data Using K-means algorithm

Author: Dr. Bushra M. Hussan
Journal: basrah journal of science البصرة للعلوم ISSN: 18140343 Year: 2012 Volume: 30 Issue: 1A english Pages: 46-56
Publisher: Basrah University جامعة البصرة

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Abstract

Data mining is one of the knowledge discovery steps in database, in which modelling techniquesare applied. In this paper, K-means method is applied for dealing with medical database forclustering. To increase the efficiency of mining process, some pre-processing need to be done to thedata. Experimental results showed the good accuracy when applied to the adjust data.


Article
Support Vector Machine Procedure as a Data Mining Multi-class Classifier
أسلوب آلة المتجه الداعم بوصفه مصنفا متعدد الحالات في تنقيب البيانات

Author: Zakariya Y. Algamal
Journal: IRAOI JOURNAL OF STATISTICAL SCIENCES المجلة العراقية للعلوم الاحصائية ISSN: 1680855X Year: 2012 Volume: 12 Issue: 22 Pages: 26-40
Publisher: Mosul University جامعة الموصل

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Abstract

AbstractSupport vector machine initially developed to perform binary classification. This paper presents a multi-class support vector machine classifier and ordinal regression to classify the type of bone mineral density. This paper compares the performance of four multi-class approaches, one-against-all, one-against-one, Weston and Watkins, and Crammer and Singer. Results from our real life data conclude that Crammer and Singer may be better approach depending on training error and the percentage of correctly classified test data. Also, we find that the training error becomes more less when the regulization parameter and kernel parameter become large.

يستخدم اسلوب الة المتجه الداعم للتصنيف الثنائي عندما يكون متغير الاستجابة ذا صفتين. يهدف هذا البحث الى تقديم مفهوم اسلوب الة المتجه الداعم للتصنيف المتعدد الحالات وكذلك الانحدار الترتيبي لتصنيف نوع كثافة العظم. يقوم هذا البحث بمقارنة اربعة اساليب من اساليب المتجه الداعم للتصنيف المتعدد الحالات OAA, OAO, WW, و CS . وقد أظهرت النتائج التي حصلنا عليها بان اسلوب CS يكون افضل اسلوب تصنيفي متعدد الحالات بالاعتماد على خطأ التدريب والنسبة المئوية للتصنيف الصحيح لمجموعة الاختبار ، كذلك وجدنا ان خطأ التدريب يصبح اقل كلما ازدات قيمة المعلمة و المعلمة .

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