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فارسی
Rojiar Pir mohammadiani

Rojiar Pir mohammadiani

Academic rank: Assistant Professor
ORCID:
Education: PhD.
ScopusId: 3216
HIndex:
Faculty: Faculty of Engineering
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Education

  • PhD. in Information Technology-Information system , Khajeh Nasir Toosi Univercity Of Technology , Iran (2012 - 2017)
    Thesis title: A Model for Evaluating Social Media Users- Product Review Web Sites
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Courses

Bachelor Of Science
Master Of Science

Research activities

Journal Papers
Diverse Joint Nonnegative Matrix Tri-Factorization for Attributed Graph Clustering Arina Mohammadi, Seyed Amjad Seyedi, Fardin Akhlaghian Tab, Rojiar Pir mohammadiani (2024)
Unsupervised feature selection using orthogonal encoder-decoder factorization Maryam Mozaffari, Seyed Amjad Seyedi, Rojiar Pir mohammadiani, Fardin Akhlaghian Tab (2024)
main components of user credit evaluation according to organizational goals in the life cycle of big data (1402)
Social Media Value Creation Practices and Interactivity of Electronic Word of Mouth System Rojiar Pir mohammadiani, Hossein AbbasiMehr, zaki malik (2023)
A method based on k-shell decomposition to identify influential nodes in complex networks bakhtyar rafigh, Rojiar Pir mohammadiani, Amir sheikh ahmedi, Bryar Rafq Hamakarim, Mehri Bahrami (2023)
Optimal stochastic self-scheduling of a water-energy virtual power plant considering data clustering and multiple storage systems Navid Rezaei, Yasin Pezhmani, Rojiar Pir mohammadiani (2023)
A novel method of spectral clustering in attributed networks by constructing parameter-free affinity matrix Kamal Berahmand, Mehrnoosh Mahmoudi, Azadeh Faroughi, Rojiar Pir mohammadiani (2022)
Spectral clustering on protein-protein interaction networks via constructing affinity matrix using attributed graph embedding Kamal Berahmand, Elahe Nasiri, Rojiar Pir mohammadiani, yuefeng Li (2021)
(1398)
Using AHP to complex network analysis tools selection Rojiar Pir mohammadiani (2019)
A Model for Investigation of the Intensity of Trust Relationships' Strength among Users in Social Media (1396)
The moderating effect of relationships’ strength on the users’ activity - users’ influence Rojiar Pir mohammadiani (2017)
BEHAVIORAL SCORING MODEL USING DATA MINING APPROACH AND ANALYTIC HIERARCHY PROCESS shahriar mohammadi, Rojiar Pir mohammadiani (2015)
Conference Papers
Enhancing Irrigation Systems in Edge-enabled IOT Environments Zana Ismael Khdhir, Zaniar Pir Mohamamdiani, Rojiar Pir mohammadiani, Sadoon Azizi (2024)
unsupervised feature selection methods based on structural particularity of minimum spanning tree Rojiar Pir mohammadiani, Maryam Mozaffari, Soma Soleimanzadeh (2022)
Inferring the Relationship between Users' Personality and their image on Flicker using deep learning and clustering Rojiar Pir mohammadiani, Hamid Sadeghi (2020)
Using the Analytical Hierarchical Process to the Selection of Complex Network Analysis Tools Rojiar Pir mohammadiani, rezvan salimi (2019)
The effects of interactivity of electronic word of mouth systems on value creation practices on social media zaki malik, Rojiar Pir mohammadiani (2019)
Cloud Based Mobile Services in Academic Environment Rojiar Pir mohammadiani, Ismail Ataie, Tania Taami (2017)
Sentence Retrieval with Sentiment-specific Topical Anchoring for Review Summarization Jiaxing Tan, Alexander Kotov, Rojiar Pir mohammadiani, Yumei Huo (2017)
Speech
Theses
Community detection of attributed networks using spectral based algorithms Saman Abdulla Hayni, Rojiar Pir mohammadiani, Alireza Abdollahpouri (2024)
The necessity of analyzing customer behavior in service industries, including internet service providers, is especially high in today's competitive environment. Understanding consumption patterns and customer value helps companies optimize their services and develop more effective marketing strategies. This research focuses on analyzing the behavior of ADSL customers in Saqqez, aiming to identify the best clustering algorithm for segmenting customers based on criteria such as consumption volume, customer type, and the RFM model (Recency, Frequency, Monetary). In this study, three clustering algorithms, KMeans, SOM, and FCM, were evaluated using real data obtained from the Kurdistan province telecommunications over a one-year period. The data included features such as purchase date, service volume, payment type, and RFM indicators. To assess the performance of the algorithms, Silhouette Score, Davies-Bouldin Index, and Calinski-Harabasz Index were used to precisely measure clustering quality and cluster differentiation. The results showed that the KMeans algorithm, with higher scores in evaluation metrics compared to other algorithms, had the best performance in clustering customers. This algorithm effectively segmented customers based on consumption volume and RFM criteria into low, medium, and high-consumption clusters. These analyses can help internet service providers offer optimized services and identify and retain high-value customers (1403)
Enhancing Irrigation Systems Using a Machine Learning Technique in Edge-enabled IoT Environments Zana Ismael Khdhir, Rojiar Pir mohammadiani, Sadoon Azizi (2024)
Community Detection with Density based Approximate Spectral Culstering for Attributed Network (1402)
Community detection by Laplacian peak centrality Community detection by Laplacian peak centrality Community detection by Laplacian peak centrality (1402)
Classification and diagnosis of breast cancer based on 3D images (1402)
Community discovery in Attributed Graphs using Community discovery in Attributed Graphs using Joint Nonnegative Matrix Tri-Factorization (1402)
Development of relative strength index and commonly used patterns in cryptocurrency trading (1401)
(1401)
پیش بینی پیوند با استفاده از شبیه ترین نود ها در جوامع مشترک در شبکه های پیچیده Elmira Jamalpour, Rojiar Pir mohammadiani (2022)
A k-shell decomposition-based method for identification of influential nodes in complex networks bakhtyar rafigh, Rojiar Pir mohammadiani (2022)
(1401)

Research interests

  • information technology
  • ُsoftware
  • Data Mining
  • Social network analysis (SNA)
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