Discussion of a master's thesis in the College of Computer Science and Mathematics
Discussion of a master's thesis in the College of Computer Science and Mathematics - Department of Computer Science entitled (Recognizing the extent of people's interest in news publications using semantic analysis)
Discussed at the College of Computer Science and Mathematics at the University of Mosul on 5/11-2021, a master's thesis tagged
Using Semantic Analysis for Location-aware Personalized News Recommendation)
For the student Adnan Abdullah Attia Mahmoud and under the supervision of Dr. Ghida Abdel Aziz Majeed
The thesis presented by the student dealt with a method for classifying complex semantic relationships on the basis of one or more relationships between entities or terms. The proposed model combines extensive logical knowledge and understanding of triple bonds and their relationship with machine learning techniques based on explicit lexical properties and implicit qualities of words to solve the task of classifying complex semantic relationship.
The database that was used in this research consisted of three topics (health, sports, economics), which consisted of 20 research papers and 1000 words for each topic, which represent real publications. A glossary was built for each topic that includes the words that have the highest frequency in that field. Chart The semantic that was extracted from these publications consists of several relationships based on the triple relationship (entity, relationship name, entity) so that a wide range of information is available.
Suggesting and designing a recommendation system that displays the news that a person prefers to hear from morning until the end of the day, excluding news that does not fall within his interests by using semantic analysis.
Chair the discussion committee
Prof. Dr. Hussein Attia Lafta from the University of Babylon / College of Science for Girls, with the membership of Prof. Dr. Ibrahim Ahmed Saleh and the teacher Dr. Ban Sharif Mustafa, under the supervision and membership of Assistant Professor Dr. Ghaida Abdulaziz Majeed