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   https://doi.org/10.1007/s41109-019-0219-z  

   Bento, José; Ioannidis, Stratis (December 2019, Applied Network Science)
2. A Family of Tractable Graph Distances

   https://doi.org/10.1137/1.9781611975321.38  

   Bento, Jose; Ioannidis, Stratis (January 2018, SIAM International Conference on Data Mining)

   Important data mining problems such as nearest-neighbor search and clustering admit theoretical guarantees when restricted to objects embedded in a metric space. Graphs are ubiquitous, and clustering and classification over graphs arise in diverse areas, including, e.g., image processing and social networks. Unfortunately, popular distance scores used in these applications, that scale over large graphs, are not metrics and thus come with no guarantees. Classic graph distances such as, e.g., the chemical and the CKS distance are arguably natural and intuitive, and are indeed also metrics, but they are intractable: as such, their computation does not scale to large graphs. We define a broad family of graph distances, that includes both the chemical and the CKS distance, and prove that these are all metrics. Crucially, we show that our family includes metrics that are tractable. Moreover, we extend these distances by incorporating auxiliary node attributes, which is important in practice, while maintaining both the metric property and tractability. 

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3. A Family of Tractable Graph Distances

   Bento, José; Ioannidis, Stratis (May 2018, Proceedings of the 2018 SIAM International Conference on Data Mining)

   Important data mining problems such as nearestneighbor search and clustering admit theoretical guarantees when restricted to objects embedded in a metric space. Graphs are ubiquitous, and clustering and classification over graphs arise in diverse areas, including, e.g., image processing and social networks. Unfortunately, popular distance scores used in these applications, that scale over large graphs, are not metrics and thus come with no guarantees. Classic graph distances such as, e.g., the chemical and the CKS distance are arguably natural and intuitive, and are indeed also metrics, but they are intractable: as such, their computation does not scale to large graphs. We define a broad family of graph distances, that includes both the chemical and the CKS distance, and prove that these are all metrics. Crucially, we show that our family includes metrics that are tractable. Moreover, we extend these distances by incorporating auxiliary node attributes, which is important in practice, while maintaining both the metric property and tractability. 

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4. A naturally appearing family of Cantorvals

   https://doi.org/10.1007/s11005-024-01847-3  

   Baake, Michael; Gorodetski, Anton; Mazáč, Jan (July 2024, Letters in Mathematical Physics)

   Abstract The aim of this note is to show the existence of a large family of Cantorvals arising in the projection description of primitive two-letter substitutions. This provides a common and naturally occurring class of Cantorvals. 

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5. Toward Family-Robot Interactions: A Family-Centered Framework in HRI

   https://doi.org/10.1145/3610977.3634976  

   Cagiltay, Bengisu; Mutlu, Bilge (March 2024, ACM)

   As robotic products become more integrated into daily life, there is a greater need to understand authentic and real-world human-robot interactions to inform product design. Across many domestic, educational, and public settings, robots interact with not only individuals and groups of users, but also families, including children, parents, relatives, and even pets. However, products developed to date and research in human-robot and child-robot interactions have focused on the interaction with their primary users, neglecting the complex and multifaceted interactions between family members and with the robot. There is a significant gap in knowledge, methods, and theories for how to design robots to support these interactions. To inform the design of robots that can support and enhance family life, this paper provides (1) a narrative review exemplifying the research gap and opportunities for family-robot interactions and (2) an actionable family-centered framework for research and practices in human-robot and child-robot interaction. 

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