hope
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Intrinsic Evaluation of Graph Embeddings: Assessing Clustering and Community Detection Performance
Abstract: This paper presents an intrinsic evaluation of some graph embedding techniques on clustering and community detection tasks. We analyze a diverse set of embedding methods, ranging from traditional techniques such as Laplacian eigenmaps to more recent approaches like graph autoencoders, high-order proximity preserved embedding (HOPE), and graph attention network (GAT), using two widely studied datasets, Cora and CiteSeer. Our evaluation relies on two main metrics: Silhouette score with respect to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 40–48 Read article
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From Hype to Hope: Analyzing Development’s Role in Social Transformation
Abstract: This paper aims to critically examine the transformative potential of development initiatives in fostering social change. While development is often hailed as a panacea for societal challenges, this study seeks to disentangle hype from the hope by assessing its real impact on social transformation. To achieve this, a systematic literature review (SLR) was conducted, analyzing a comprehensive range of peer-reviewed articles, reports, and case studies published over the last two …
Published in International Journal of Urban Design and Development · Vol. 2, Issue 2, 2024 · pp. 48–55 Read article