User interest finding relevant information based on recommendations system /
Ibrahim Mahmoud Emara
User interest finding relevant information based on recommendations system / إستخدام الانظمة المقترحة من اجل العثورعلى المعلومات ذات الصلة Ibrahim Mahmoud Emara ; Supervised Mahmood Abdelmoneim , Mervat Gheith - Cairo : Ibrahim Mahmoud Emara , 2018 - 75 Leaves : charts ; 30cm
The change Institute of Statistical Studies and Researches to Faculty Graduate Studies for Statistical Research
Thesis (M.Sc.) - Cairo University - Institute of Statistical Studies and Researches - Department of Information Systems and Technology
In the World, Today Data Scientist Become the Sixth Job of the 21st Century (jobtrends-Data-Scientist, n.d.) The Main Description for That is using Data Mining Techniques and Statistical Modeling to Find Hidden Questions in Large Dataset for Making Good Prediction for The Future to Get A Good Decision. As a Part of Data Scientist Job Working in Recommended Systems Using Its Techniques Like Collaborative Filtering and Content-Based for Making Good Recommendation to Users. Today Digital Information Produce Every Day, News Products, Jobs, Movies, Book So Finding Interesting Things to User May Be Difficult. Recommender System is A Good Tool for That, Here We Will Talk About Most Algorithms Used in Recommender System Like (Collaborative Filtering, Content-Based). Collaborative Filtering is to Finding Users Similar to Each Other or Items Belong on Similarity Users or Items Rating. Content-Based Is Finding Similar User Based on Similar User Profiles, Cold Start Problem Appear When New User Get Login in The System It is Hard to Find Similar Users Because There is no Enough Information at The Beginning of The Recommendation Systems First Run to Make Similarity Between Users. Shilling Attack People Allow Ratings People May Poll A Lot of Positive Ratings for Their Own Items and Negative Ratings for Their Concurrent. (wikipedia-Collaborative_filtering, n.d.) As a Result, This Data Can Be Utilized to Move Forward the Execution of Current Recommender Systems, Since the Current Estimation Concentrated of The Client Can Be Utilized as an Extra Parameter in Conjunction with The User's Profile Data to Decide the Foremost Fitting Substance to Send in a Proposal Message Using Sentiment Analysis. Sentiment Analysis is Automated Operation to Understanding an Opinion About A Specific Matter from Written or Spoken Language. 2.5 Quintillion Bytes of Data Every Day Are Created, Sentiment analysis has Become A Key System for Making Meaning of That Data
Collaborative Filtering (CF) Information based Recommendations system
User interest finding relevant information based on recommendations system / إستخدام الانظمة المقترحة من اجل العثورعلى المعلومات ذات الصلة Ibrahim Mahmoud Emara ; Supervised Mahmood Abdelmoneim , Mervat Gheith - Cairo : Ibrahim Mahmoud Emara , 2018 - 75 Leaves : charts ; 30cm
The change Institute of Statistical Studies and Researches to Faculty Graduate Studies for Statistical Research
Thesis (M.Sc.) - Cairo University - Institute of Statistical Studies and Researches - Department of Information Systems and Technology
In the World, Today Data Scientist Become the Sixth Job of the 21st Century (jobtrends-Data-Scientist, n.d.) The Main Description for That is using Data Mining Techniques and Statistical Modeling to Find Hidden Questions in Large Dataset for Making Good Prediction for The Future to Get A Good Decision. As a Part of Data Scientist Job Working in Recommended Systems Using Its Techniques Like Collaborative Filtering and Content-Based for Making Good Recommendation to Users. Today Digital Information Produce Every Day, News Products, Jobs, Movies, Book So Finding Interesting Things to User May Be Difficult. Recommender System is A Good Tool for That, Here We Will Talk About Most Algorithms Used in Recommender System Like (Collaborative Filtering, Content-Based). Collaborative Filtering is to Finding Users Similar to Each Other or Items Belong on Similarity Users or Items Rating. Content-Based Is Finding Similar User Based on Similar User Profiles, Cold Start Problem Appear When New User Get Login in The System It is Hard to Find Similar Users Because There is no Enough Information at The Beginning of The Recommendation Systems First Run to Make Similarity Between Users. Shilling Attack People Allow Ratings People May Poll A Lot of Positive Ratings for Their Own Items and Negative Ratings for Their Concurrent. (wikipedia-Collaborative_filtering, n.d.) As a Result, This Data Can Be Utilized to Move Forward the Execution of Current Recommender Systems, Since the Current Estimation Concentrated of The Client Can Be Utilized as an Extra Parameter in Conjunction with The User's Profile Data to Decide the Foremost Fitting Substance to Send in a Proposal Message Using Sentiment Analysis. Sentiment Analysis is Automated Operation to Understanding an Opinion About A Specific Matter from Written or Spoken Language. 2.5 Quintillion Bytes of Data Every Day Are Created, Sentiment analysis has Become A Key System for Making Meaning of That Data
Collaborative Filtering (CF) Information based Recommendations system