Fouille d’épisodes à partir de données incertaines (Episode mining from uncertain data)

الموضوعات

علوم تطبيقية وتكنولوجية

الملخص

Data mining is a critical process in the discovery of knowledge from data. Its primary objectiveis to extract interesting patterns that implicitly indicate significant relationships betweenitems. Different branches of data mining manipulate various types of data. Episode mining isa subfield of data mining that aims to uncover valuable knowledge from temporal data in theform of a single, long sequence of events. The sequence may not always certain data; it maybe noisy, sourced from multiple sources, or collected with errors. Consequently, there is a needto develop and design algorithms to extract frequent episodes from uncertain data. This thesisproposes novel algorithms for frequent episode and episode rule mining in the case of certaindata and addresses also the challenges associated with these tasks in the context of uncertain

روابط وملفات

التعريف والنوع

رقم الوثيقة

f2ca7cd9-1967-4158-92ce-634238b185a6

رقم العقد

0

نوع الوسائط

Crawler

نوع المحتوى

الرسائل العلمية

صيغة المصدر

رسائل دكتوراة

نوع الملف

pdf text

أسماء الملفات

792186_1.pdf

بيانات النشر

ألقاب المؤلفين

[{"name_ar":"Nouioua Farid ","title_ar":"اشراف","title_en":"Supervision"},{"name_ar":"Ouarem Oualid","title_ar":"اعداد","title_en":"Preparation"},{"name_ar":"Philippe Fournier-Viger","title_ar":"اشراف","title_en":"Supervision"}]

اللغة

French

المصدر والدورية

اسم المصدر

Fouille d’épisodes à partir de données incertaines (Episode mining from uncertain data)

المحتوى والصفحات

عدد الصفحات

0

كلمات الباحثين

Episode mining, episode rules, NONEPI, EMDO, UEMDO, prediction, uncertaindata

إشراف وإعداد

الإشراف

Nouioua Farid , Philippe Fournier-Viger

الإعداد

Ouarem Oualid

الاقتباسات الببليوغرافية