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A Survey of Methods for Explaining Black Box Models
TLDR
A classification of the main problems addressed in the literature with respect to the notion of explanation and the type of black box system is provided to help the researcher to find the proposals more useful for his own work.
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Trajectory pattern mining
TLDR
This paper develops an extension of the sequential pattern mining paradigm that analyzes the trajectories of moving objects and introduces trajectory patterns as concise descriptions of frequent behaviours in terms of both space and time.
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WhereNext: a location predictor on trajectory pattern mining
TLDR
This paper proposes WhereNext, which is a method aimed at predicting with a certain level of accuracy the next location of a moving object, which uses previously extracted movement patterns named Trajectory Patterns, which are a concise representation of behaviors of moving objects as sequences of regions frequently visited with a typical travel time.
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Human mobility, social ties, and link prediction
TLDR
It is shown that mobility measures alone yield surprising predictive power, comparable to traditional network-based measures, and the prediction accuracy can be significantly improved by learning a supervised classifier based on combined mobility and network measures.
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DEMON: a local-first discovery method for overlapping communities
TLDR
A simple local-first approach to community discovery, able to unveil the modular organization of real complex networks, by democratically letting each node vote for the communities it sees surrounding it in its limited view of the global system.
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Local Rule-Based Explanations of Black Box Decision Systems
TLDR
This paper proposes LORE, an agnostic method able to provide interpretable and faithful explanations for black box outcome explanation, and shows that LORE outperforms existing methods and baselines both in the quality of explanations and in the accuracy in mimicking the black box.
View PDF on arXiv
Returners and explorers dichotomy in human mobility
TLDR
It is shown that returners and explorers play a distinct quantifiable role in spreading phenomena and that a correlation exists between their mobility patterns and social interactions.
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Visually driven analysis of movement data by progressive clustering
TLDR
The paper investigates the possibilities of using clustering techniques in visual exploration and analysis of large numbers of trajectories, that is, sequences of time-stamped locations of some moving entities, and suggests the procedure of progressive clustering where a simple distance function with a clear meaning is applied on each step which leads to easily interpretable outcomes.
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Interactive visual clustering of large collections of trajectories
TLDR
This work proposes an approach to extracting meaningful clusters from large databases by combining clustering and classification, which are driven by a human analyst through an interactive visual interface.
View on IEEE
Mobility, Data Mining and Privacy - Geographic Knowledge Discovery
TLDR
This book tightly integrates and relates their findings in 13 chapters covering all related subjects, including the concepts of movement data and knowledge discovery from movement data; privacy-aware geographic knowledge discovery; wireless network and next-generation mobile technologies; trajectory data models, systems and warehouses; privacy and security aspects of technologies and related regulations.
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