0% Complete
Home
/
11th International Conference on Computer and Knowledge Engineering
GroupRec: Group Recommendation by Numerical Characteristics of Groups in Telegram
Authors :
Davod Karimpour
1
Mohammad Ali Zare Chahooki
2
Ali Hashemi
3
1- Computer Engineering Department, Yazd University, Yazd, Iran
2- Computer Engineering Department, Yazd University, Yazd, Iran
3- Computer Engineering Department, Yazd University, Yazd, Iran
Keywords :
Recommendation of social groups, Telegram, social networks (online), computational modeling, business.
Abstract :
Today, recommender systems are used in many different businesses to find items of interest to users. The use of these systems is widely found in online economic systems and social networks. Therefore, using these systems in the messaging environment will cause changes and transformations for marketing. Telegram is a cloud-based messenger with more than 500 million monthly active users. This messenger has a relatively acceptable position compared to its other competitors, because the security and features provided in it, have made it different from other messengers and close to social networks. One of the most popular features of messengers is groups. Many marketers are looking for groups that fit their field. One of the main gaps in the messengers regarding advertising and marketing to expand businesses is the impossibility of finding social groups. In this paper, a new method for group recommendation in the Telegram is presented. This method, by receiving a set of users, analyzes their groups and recommends a list of ranked groups. The proposed method is created by combining the previous two methods in the field of group recommendation and computational modeling of numerical variables obtained from each group. This study is dependent on the information of all users due to the use of the membership graph, and the behavior of the system changes by the information extracted from the users. The results of experimental experiments show a significant reduction of RMSE and MAE in the proposed method compared to the previous two methods.
Papers List
List of archived papers
IranITJobs2021: a Dataset for Analyzing Iranian Online IT Job Advertisements Collected Using a New Crowdsourcing Process
Fakhroddin Noorbehbahani - Nikta Akbarpour - Mohammad Reza Saeidi
Attention-Boosted Ensemble of Pre-trained Convolutional Neural Networks for Accurate Diabetic Retinopathy Detection
Benyamin Mirab Golkhatmi - Mohammad Hossein Moattar
New Design of Efficient Reversible Quantum Saturation Adder
Negin Mashayekhi - Mohammad Reza Reshadinezhad - Shekoofeh Moghimi
Improving Motor Imagery Classification in BCI Systems Using EMD and Multi-Layer CNNs
Reza Arghand - Ali Chaibakhsh - Moein Radman
Hybrid navigation based on GPS data and SIFT-based place recognition using Biologically-inspired SLAM
Sahar Salimpour Kasebi - Hadi Seyedarabi - Javad Musevi Niya
An Efficient Planning Method for Autonomous Navigation of a Wheeled-Robot based on Deep Reinforcement Learning
Ali Salimi Sadr - Mahdi Shahbazi Khojasteh - Hamed Malek - Armin Salimi-Badr
Automated software design using Machine Learning With Natural Language Processing
Fahimeh Khedmatkon - Seyed Mohammad Hossein Hasheminejad - Jaleh Shoshtarian Malak
Towards Efficient Capsule Networks through Approximate Squash Function and Layer-wise Quantization
Mohsen Raji - Kimia Soroush - Amir Ghazizadeh
A New Application of Machine Learning Based Methods for Disk Space Variation Fault Diagnosis in Transformer Windings
Reza Behkam - Amir Lotfi - Gevork B. Gharehpetian
A Novel Deformable Registration Method for Cerebral Magnetic Resonance Images
Bahareh Asadpour Dasht Bayaz - Mahdi Saadatmand - Fabrice Wallois
more
Samin Hamayesh - Version 41.7.6