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تنقيب المعلومات التعليمي
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Added by
Damascus University حلقة بحث
Publication date
2018
fields
Informatics Engineering
and research's language is
العربية
Created by
Mirna Arbach
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تنقيب المعلومات التعليمي : هو عملية تحويل المعلومات الخام القادمة من الأنظمة التعليمية الى معلومات مفيدة يمكن استخدامها من قبل مطورين الأنظمة التعليمية والطلاب والمعلمين و حتى الباحثين في مجال التعليم نظم هذا البحث على فصلين : 1 -التعرف على منهجيات الDM المستخدمة في المجال التعليمي و التحدث عن بعض التطبيقات باستخدام هذه المنهجيات. 2 -التحدث بشكل مفصل عن مشكلة التنبؤ بأداء الطلاب و عرض بعض الطرق الكلاسيكية المستخدمة لحل هذه المشكلة ثم عرض النموذج المقترح باستخدام أنظمة التوصية.
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References used
Recommender System for Predicting Student Performance
E-Learning Using Data Mining
Data Mining for Education
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Data mining is becoming a pervasive technology in activities as diverse as using historical data to predict the success of a marketing campaign looking for patterns in financial transactions to discover illegal activities. From this perspective it wa
s just a matter of time for the discipline to reach the important area of computer security This research presents a collection of research efforts on the use of data mining in computer security.
The advances in location-acquisition and mobile computing techniques have generated massive spatial trajectory data, which represent the mobility of a diversity of moving objects, such as people, vehicles and animals. Many techniques have been propos
ed for processing, managing and mining trajectory data in the past decade, fostering a broad range of applications. In this article, we conduct a systematic survey on the major research into trajectory data mining, providing a panorama of the field as well as the scope of its research topics. Following a roadmap from the derivation of trajectory data, to trajectory data preprocessing, to trajectory data management, and to a variety of mining tasks (such as trajectory pattern mining, outlier detection, and trajectory classification), the survey explores the connections, correlations and differences among these existing techniques. This survey also introduces the methods that transform trajectories into other data formats, such as graphs, matrices, and tensors, to which more data mining and machine learning techniques can be applied. Finally, some public trajectory datasets are presented. This survey can help shape the field of trajectory data mining, providing a quick understanding of this field to the community.
This research presents literature review on using Artificial intelligence and Data Mining techniques in Anti Money Laundering systems. We compare many methodologies used in different research papers with the purpose of shedding some light on real life applications using Artificial intelligence
. تعد إدارة وفهم بيانات المواقع المجمعة قضيتين مهمتين لهذه التطبيقات. تقدم هذه الورقة طرقًا لاستخراج مواقع مثيرة للاهتمام من البيانات المكانية والزمانية. الهدف من هذه الورقة هو تجميع آثار GPS الفردية للحصول على رؤى عن الأماكن المثيرة للاهتمام. يمكن ا
لحصول على هذه المواقع المهمة من خلال معالجة البيانات من الأجهزة التي تعمل بنظام GPS للمستخدمين الذين يعيشون في منطقة جغرافية معينة.
In this paper we introduce a comparison for some of data mining algorithm for traffic accidents analysis.
We start by describing available data for entry by analyzing the structure of statistical reports in Lattakia traffic directorate, and proceed
to data mining stage which enables us to smart study of factors that play roles in traffic accident and find its inter-relations and importance for causing traffic accident.
That comes after building data warehouse upon the database we built to store the data we gathered.
In this research we list a some of models was tested which is a sample of a many cases we checked to have the research results.
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