Yazar "Coskun, Mustafa" için listeleme
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Consensus embedding for multiple networks: Computation and applications
Li, Mengzhen; Coskun, Mustafa; Koyuturk, Mehmet (CAMBRIDGE UNIV PRESS32 AVENUE OF THE AMERICAS, NEW YORK, NY 10013-2473, 2022)Machine learning applications on large-scale network-structured data commonly encode network information in the form of node embeddings. Network embedding algorithms map the nodes into a lowdimensional space such that the ... -
Developing a label propagation approach for cancer subtype classification problem
Guner, Pinar; Bakir-Gungor, Burcu; Coskun, Mustafa (TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEYATATURK BULVARI NO 221, KAVAKLIDERE, ANKARA 00000, TURKEY, 2022)Cancer is a disease in which abnormal cells grow uncontrollably and invade other tissues. Several types of cancer have various subtypes with different clinical and biological implications. Based on these differences, ... -
Fast computation of Katz index for efficient processing of link prediction queries
Coskun, Mustafa; aggag, Abdelkader; Koyuturk, Mehmet (SPRINGERVAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS, 2021)Network proximity computations are among the most common operations in various data mining applications, including link prediction and collaborative filtering. A common measure of network proximity is Katz index, which has ... -
Integrated querying and version control of context-specific biological networks
Cowman, Tyler; Coskun, Mustafa; Grama, Ananth; Koyuturk, Mehmet (OXFORD UNIV PRESS, GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND, 2020)Motivation: Biomolecular data stored in public databases is increasingly specialized to organisms, context/pathology and tissue type, potentially resulting in significant overhead for analyses. These networks are often ... -
Intrinsic graph topological correlation for graph convolutional network propagation
Coskun, Mustafa (ELSEVIER, 2022)Recently, Graph Convolutional Networks (GCNs) and their variants become popular to learn graph-related tasks. These tasks include link prediction, node classification, and node embedding, among many others. In the node ... -
Linear vs. Non-Linear Embedding Methods in Recommendation Systems
Gurler, Kerem; Coskun, Mustafa; Karagenc, Safak; Orun, Gokhan; Pak, Burcu Kuleli; Gungor, Vehbi Cagri (Institute of Electrical and Electronics Engineers Inc., 2022)Predicting customer interest in items is very crucial in direct marketing as it can potentially boost sales. Data mining techniques are developed to predict which items a particular user might be interested in based on ... -
Node similarity-based graph convolution for link prediction in biological networks
Coskun, Mustafa; Koyuturk, Mehmet (OXFORD UNIV PRESSGREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND, 2021)Background: Link prediction is an important and well-studied problem in network biology. Recently, graph representation learning methods, including Graph Convolutional Network (GCN)-based node embedding have drawn increasing ... -
OFFER : Referees Suggester for the Journal Editors
Coskun, Mustafa; Hacilar, Hilal; Gezer, Cengiz; Gungor, Vehbi Cagri (IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2019)Assigning appropriate referees to a journal or conference paper is a vital task for many reasons, including enhancing the journal venue quality and reliance, fair judgement of the papers, and among many others. While ... -
Topological feature generation for link prediction in biological networks
Temiz, Mustafa; Bakir-Gungor, Burcu; Sahan, Pinar Guner; Coskun, Mustafa (PEERJ INC, 2023)Graph or network embedding is a powerful method for extracting missing or potential information from interactions between nodes in biological networks. Graph embedding methods learn representations of nodes and interactions ... -
Traffic Light Management Systems Using Reinforcement Learning
Can, Sultan Kubra; Thahir, Adam; Coskun, Mustafa; Gungor, Vehbi Cagri (Institute of Electrical and Electronics Engineers Inc., 2022)While reducing traffic congestion and decrease the number of traffic accidents in the intersections, most of the traffic light management approaches cannot adapt well to fast changing traffic dynamics and growing demands ...
