پديد آورنده :
رمضاني، رضا
عنوان :
پيداكردن قوانين همبستگي در داده هاي پيوندي
مقطع تحصيلي :
كارشناسي ارشد
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان، دانشكده برق و كامپيوتر
صفحه شمار :
چهارده، 108ص.: مصور، جدول، نمودار
يادداشت :
ص.ع. به فارسي و انگليسي
استاد راهنما :
محمدحسين سرايي، محمدعلي نعمت بخش
توصيفگر ها :
داده كاوي , كاوش قوانين همبستگي , كاوش داده هاي وب فضايي , كاوش مجموعه عناصر مكرر
تاريخ نمايه سازي :
6/9/91
استاد داور :
رسول موسوي، عبدالرضا ميرزايي
تاريخ ورود اطلاعات :
1396/09/21
رشته تحصيلي :
برق و كامپيوتر
دانشكده :
مهندسي برق و كامپيوتر
چكيده فارسي :
به فارسي و انگليسي: قابل رويت در نسخه ديجيتالي
چكيده انگليسي :
Finding Association Rules in Linked Data Reza Ramezani R Ramezani@ec iut ac ir September 10 2012 Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan 84156 83111 IranDegree M ScMohammad Hossein Saraee Saraee@cc iut ac irMohammad Ali Nematbakhsh Nematbakhsh@eng ui ac irAbstractThe goal of this project is to propose a novel method in mining association rules from semanticweb data and linked data Association rule mining techniques need transaction in order to mineassociation rules But in semantic web data there is exact definition of transaction All researchesthat had done on mining association rules from semantic web data so far by user assistance launchto define transactions from semantic web data which this needs the user be familiar with semanticweb structure and used data domain Thus a new method is required to mine association rules fromsemantic web data without any need to transaction and also without end user involvement Forsatisfying this requirement a system had implemented in order to directly mine association rulesfrom semantic web data regardless to transaction concept and also without user involvement Thissystem consists three phases generating 2 large itemset base on entities and their relations generating larger itemsets and finally generating association rules base on large itemsets Thissystem also is able to mine association rules from a dataset that has generated from linked dataconcatenation Regard to workflow and structure of this system mining association rules fromsemantic web data only demands a dataset that consists triples The obtained results show that theproposed method without user involvement can directly mine association rules from semantic webdata and indirectly mine association rules from linked data KeywordsData Mining Association Rules Mining Semantic Web Data Mining Linked DataMining Frequent Itemset Mining
استاد راهنما :
محمدحسين سرايي، محمدعلي نعمت بخش
استاد داور :
رسول موسوي، عبدالرضا ميرزايي
