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Malamati Louta

Researcher at University of Western Macedonia

Publications -  111
Citations -  810

Malamati Louta is an academic researcher from University of Western Macedonia. The author has contributed to research in topics: Computer science & WiMAX. The author has an hindex of 13, co-authored 88 publications receiving 726 citations. Previous affiliations of Malamati Louta include Harokopio University & National Technical University of Athens.

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A Trust-Aware System for Personalized User Recommendations in Social Networks

TL;DR: A framework for handling trust in social networks is introduced, which is based on a reputation mechanism that captures the implicit and explicit connections between the network members, analyzes the semantics and dynamics of these connections, and provides personalized user recommendations to the networkMembers.
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Architectures and Bandwidth Allocation Schemes for Hybrid Wireless-Optical Networks

TL;DR: This survey endeavors to classify the main features of wireless-optical integration and provides a comprehensive compilation of the latest architectures, integrated technologies, QoS features, and dynamic bandwidth allocation (DBA) schemes.
Journal ArticleDOI

An intelligent agent negotiation strategy in the electronic marketplace environment

TL;DR: This work proposes a dynamic multi-lateral negotiation model and constructs an efficient negotiation strategy based on a ranking mechanism that does not require a complicated rationale on behalf of the buyer agents to reach an agreement aiming to maximise their owner’s utility.
Proceedings ArticleDOI

A Study on Social Network Metrics and Their Application in Trust Networks

TL;DR: In order to better understand the properties of links and the dynamics of social networks, this work distinguishes between permanent and transient links and in the latter case, it considers the link freshness.
Proceedings ArticleDOI

Traffic forecasting in cellular networks using the LSTM RNN

TL;DR: A Neural Network that can identify recurrent patterns in various metrics which can be then used for cellular network traffic forecasting and this approach offers a solution for service providers to enhance cellular network performance, by utilizing effectively the available resources.