Improving the Analysis of Context-Aware Information via Marker-Based Stigmergy and Differential Evolution

Cimino, Mario G. C. A.; Lazzeri, Alessandro; Vaglini, Gigliola

doi:10.1007/978-3-319-19369-4_31

Cited by 20 publications

(19 citation statements)

References 9 publications

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“…In order to measure such phenomenon by using call data we can collect the time and locations of each call occurred during the day to model the daily users' mobility. The similarity between refugees' and locals' mobility patterns can be computed by using the principle of stigmergy [49].…”

Section: Related Workmentioning

confidence: 99%

Assessing Refugees’ Integration via Spatio-Temporal Similarities of Mobility and Calling Behaviors

Alfeo

Cimino

Lepri

et al. 2019

IEEE Trans. Comput. Soc. Syst.

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In Turkey the increasing tension, due to the presence of 3.4 million Syrian refugees, demands the formulation of effective integration policies. Moreover, their design requires tools aimed at understanding the integration of refugees despite the complexity of this phenomenon.In this work, we propose a set of metrics aimed at providing insights and assessing the integration of Syrians refugees, by analyzing a real-world Call Details Records (CDRs) dataset including calls from refugees and locals in Turkey throughout 2017. Specifically, we exploit the similarity between refugees' and locals' spatial and temporal behaviors, in terms of communication and mobility in order to assess integration dynamics.Together with the already known methods for data analysis, we use a novel computational approach to analyze spatiotemporal patterns: Computational Stigmergy, a bio-inspired scalar and temporal aggregation of samples. Computational Stigmergy associates each sample to a virtual pheromone deposit (mark). Marks in spatiotemporal proximity are aggregated into functional structures called trails, which summarize the spatiotemporal patterns in data and allows computing the similarity between different patterns.According to our results, collective mobility and behavioral similarity with locals have great potential as measures of integration, since they are: (i) correlated with the amount of interaction with locals; (ii) an effective proxy for refugee's economic capacity, thus refugee's potential employment; and (iii) able to capture events that may disrupt the integration phenomena, such as social tensions.

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Section: Related Workmentioning

confidence: 99%

Assessing Refugees’ Integration via Spatio-Temporal Similarities of Mobility and Calling Behaviors

Alfeo

Cimino

Lepri

et al. 2019

IEEE Trans. Comput. Soc. Syst.

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“…In marker-based stigmergy (Parunak, 2006) volatile substances, such as pheromones, maintain the information locally for other individual to perceive. In computer science, marker-based stigmergy can be employed as a powerful computing paradigm exploiting both spatial and temporal dynamics, because it intrinsically embodies the time domain (Cimino, 2015). Moreover, marker-based stigmergy can be considered a computational black box modelling approach, because no domain model is assumed at design time and then results are not directly interpretable.…”

Section: Biologically-inspired Data Analysismentioning

confidence: 99%

“…Since different indicators in different Regions have different dynamics, manual adaptation is very timeconsuming, human-intensive and error-prone (Ciaramella, 2010). In this section, we first describe the role of each parameter in the processing, and then we adopt a supervised optimization based on DE, an evolutionary technique for numerical optimization problems (Cimino, 2015). The mark extension (ε) controls the distance of interaction between marks.…”

Section: The Adapting Subsystemmentioning

confidence: 99%

An Adaptive Stigmergy-based System for Evaluating Technological Indicator Dynamics in the Context of Smart Specialization

Alfeo

Appio

Cimino

et al. 2016

Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods

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Regional innovation is more and more considered an important enabler of welfare. It is no coincidence that the European Commission has started looking at regional peculiarities and dynamics, in order to focus Research and Innovation Strategies for Smart Specialization towards effective investment policies. In this context, this work aims to support policy makers in the analysis of innovation-relevant trends. We exploit a European database of the regional patent application to determine the dynamics of a set of technological innovation indicators. For this purpose, we design and develop a software system for assessing unfolding trends in such indicators. In contrast with conventional knowledge-based design, our approach is biologically-inspired and based on self-organization of information. This means that a functional structure, called track, appears and stays spontaneous at runtime when local dynamism in data occurs. A further prototyping of tracks allows a better distinction of the critical phenomena during unfolding events, with a better assessment of the progressing levels. The proposed mechanism works if structural parameters are correctly tuned for the given historical context. Determining such correct parameters is not a simple task since different indicators may have different dynamics. For this purpose, we adopt an adaptation mechanism based on differential evolution. The study includes the problem statement and its characterization in the literature, as well as the proposed solving approach, experimental setting and results.

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“…The one with the best value remains in the next generation and the other is discarded. The interested reader can refer to Cimino et al ( 2015 ) for further information on the parameterization and the behavior of DE.…”

Section: Fitting Renyi's and Marcellin's Entropies To Randomness Jmentioning

confidence: 99%

Modeling the Overalternating Bias with an Asymmetric Entropy Measure

et al. 2016

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Psychological research has found that human perception of randomness is biased. In particular, people consistently show the overalternating bias: they rate binary sequences of symbols (such as Heads and Tails in coin flipping) with an excess of alternation as more random than prescribed by the normative criteria of Shannon's entropy. Within data mining for medical applications, Marcellin proposed an asymmetric measure of entropy that can be ideal to account for such bias and to quantify subjective randomness. We fitted Marcellin's entropy and Renyi's entropy (a generalized form of uncertainty measure comprising many different kinds of entropies) to experimental data found in the literature with the Differential Evolution algorithm. We observed a better fit for Marcellin's entropy compared to Renyi's entropy. The fitted asymmetric entropy measure also showed good predictive properties when applied to different datasets of randomness-related tasks. We concluded that Marcellin's entropy can be a parsimonious and effective measure of subjective randomness that can be useful in psychological research about randomness perception.

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Improving the Analysis of Context-Aware Information via Marker-Based Stigmergy and Differential Evolution

Cited by 20 publications

References 9 publications

Assessing Refugees’ Integration via Spatio-Temporal Similarities of Mobility and Calling Behaviors

Assessing Refugees’ Integration via Spatio-Temporal Similarities of Mobility and Calling Behaviors

An Adaptive Stigmergy-based System for Evaluating Technological Indicator Dynamics in the Context of Smart Specialization

Modeling the Overalternating Bias with an Asymmetric Entropy Measure

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