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Proceedings of the XII Brazilian Symposium on Information Systems on Brazilian Symposium on Information Systems: Information Systems in the Cloud Computing Era - Volume 1

作者： Vitor Lourenco Paulo Mann Aline Paes Daniel Oliveira Universidade Federal Fluminense

ISBN: (纸本)9788576693178

The growing of criminality in Brazilian cities is a common theme addressed by media as well as by the legal authorities. To effectively reduce the criminality, people and infrastructure must be carefully involved to not only punish who had committed crimes, but also predict and prevent it. Since acquiring official data about crimes is far from trivial, citizens have become important data sources through Web-based collaborative systems. These systems provide a huge volume of data that has to be analyzed. How to analyze this volume of data and identify patterns in crimes is an important, yet open, issue. Thus, this work presents a system called SiAPP. Its main objective is to support the analysis and prediction of crime patterns using a machine learning algorithm. SiAPP automatically acquires data from collaborative sources, generate logical rules and visualizes the found patterns. Experimental analysis shows that SiAPP is a promising solution tool to assist crimes prevention.

关键词： Crime Pattern Visualization inductive logic programming Crime Analytics

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Experience-based Learning of Symbolic Numerical Constraints

Experience-based Learning of Symbolic Numerical Constraints

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IEEE-RAS International Conference on Humanoid Robots

作者： Gokhan Solak Abdullah Cihan Ak Sanem Sariel Artificial Intelligence and Robotics Laboratory Computer Engineering Department Istanbul Technical University

ISBN: (纸本)9781509047192

Learning symbolic-level numerical constraints is key to use abstractions in effective reasoning and transfer of knowledge for robot systems. We investigate this problem in an experience-based learning framework which uses inductive logic programming as the learning method. Our particular focus is on learning numerical constraints which is an open issue for ILP systems. Some approaches overcome this by using background knowledge given by domain experts. However, using expert knowledge is both expensive and domain dependent. To obtain more general solutions, numerical constraints should be induced by the robot system itself. For this purpose, we present a constraint induction method based on lazy evaluation, designed for deriving general numerical constraints from observations. We extend Aleph, an existing ILP system based on inverse entailment, with a constraint induction approach using a constraint solver. We analyze our method on some sample scenarios and demonstrate the cases where our method can induce the target concept while the prior lazy evaluation method cannot. Our results indicate that our method can generalize numerical constraints by the self observations of robots.

关键词： Experience-based learning inductive logic programming Numerical reasoning in robots

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A logic programming approach to predict effective compiler settings for embedded software

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THEORY AND PRACTICE OF logic programming 2015年第4-5期15卷 481-494页

作者： Blackmore, Craig Ray, Oliver Eder, Kerstin Univ Bristol Dept Comp Sci Bristol BS8 1UB Avon England

This paper introduces a new logic-based method for optimising the selection of compiler flags on embedded architectures. In particular, we use inductive logic programming (ILP) to learn logical rules that relate effective compiler flags to specific program features. Unlike earlier work, we aim to infer human-readable rules and we seek to develop a relational first-order approach which automatically discovers relevant features rather than relying on a vector of predetermined attributes. To this end we generated a data set by measuring execution times of 60 benchmarks on an embedded system development board and we developed an ILP prototype which outperforms the current state-of-the-art learning approach in 34 of the 60 benchmarks. Finally, we combined the strengths of the current state of the art and our ILP method in a hybrid approach which reduced execution times by an average of 8% and up to 50% in some cases.

关键词： inductive logic programming embedded system compiler optimisation

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Progressive datacenter recovery over optical core networks after a large-scale disaster

Progressive datacenter recovery over optical core networks a...

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International Workshop on Design of Reliable Communication Networks (DRCN)

作者： Sifat Ferdousi Ferhat Dikbiyik Massimo Tornatore Biswanath Mukherjee University of California Davis USA Sakarya University Turkey Politecnico di Milano Italy

Today's cloud system are composed of geographically distributed datacenter interconnected by high-speed optical networks. Disaster failures can severely affect both the communication network as well as datacenters infrastructure and prevent users from accessing cloud services. After large-scale disasters, recovery efforts on both network and datacenters may take days, and, in some cases, weeks or months. Traditionally, the repair of the communication network has been treated as a separate problem from the repair of datacenters. While past research has mostly focused on network recovery, how to efficiently recover a cloud system jointly considering the limited computing and networking resources has been an important and open research problem. In this work, we investigate the problem of progressive datacenter recovery after a large-scale disaster failure, given that a network-recovery plan is made. An efficient recovery plan is explored to determine which datacenters should be recovered at each recovery stage to maximize cumulative content reachability from any source considering limited available network resources. We devise an Integer Linear Program (ILP) formulation to model the associated optimization problem. Our numerical examples using the ILP show that an efficient progressive datacenter-recovery plan can significantly help to increase reachability of contents during the network recovery phase. We succeeded in increasing the number of important contents in the early stages of recovery compared to a random-recovery strategy with a slight increase in resource consumption.

关键词： core network data center networks(communications) recovery plan Disasters Web resources inductive logic programming large sizes Accessibility Research Problems Resource utilization

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Speeding up operations on feature terms using constraint programming and variable symmetry

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ARTIFICIAL INTELLIGENCE 2015年 220卷 104-120页

作者： Ontanon, Santiago Meseguer, Pedro Drexel Univ Dept Comp Sci Philadelphia PA 19104 USA IIIA CSIC Artificial Intelligence Res Inst Spanish Council Sci Res Bellaterra 08193 Catalonia Spain

Feature terms are a generalization of first-order terms which have recently received increased attention for their usefulness in structured machine learning, natural language processing and other artificial intelligence applications. One of the main obstacles for their wide usage is that, when set-valued features are allowed, their basic operations (subsumption, unification, and antiunification) have a very high computational cost. We present a Constraint programming formulation of these operations, which in some cases provides orders of magnitude speed-ups with respect to the standard approaches. In addition, exploiting several symmetries that often appear in feature terms databases causes substantial additional savings. We provide experimental results of the benefits of this approach. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Feature terms Constraint programing Symmetries Structured machine learning inductive logic programming

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Joint Topology Design and Mapping of Service Function Chains in Network Function Virtualization

Joint Topology Design and Mapping of Service Function Chains...

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IEEE Global Communications Conference

作者： Zilong Ye Xiaojun Cao Chunming Qiao California State University Georgia State University University at Buffalo SUNY

ISBN: (纸本)9781509013296

Network Function Virtualization (NFV) is promising to lower the network operator's capital expenditure and operational expenditure by replacing proprietary hardware-based network equipment with software-based virtual network functions that can be consolidated into telecom clouds. In particular, NFV provides an efficient way to deploy network services using service function chains that consist of a set of virtual network functions interconnected by virtual links. A practical and yet theoretically challenging issue related to NFV Management and Orchestration is how to jointly optimize the topology design and mapping of multiple service function chains, which is called the JTDM problem. In this paper, we develop an Integer Linear programming (ILP) model to formulate the JTDM problem with the objective of minimizing the bandwidth consumption in the physical substrate. We propose a novel heuristic algorithm, namely Closed-loop with Critical Mapping Feedback (CCMF), to efficiently address this problem. Through comprehensive simulations, we demonstrate that the CCMF algorithm is efficient in terms of the bandwidth consumption in various scenarios, and can achieve a bandwidth consumption that is close to the minimum obtained by ILP.

关键词： Network function virtualization Service function chain Topology design Mapping MAPPING(MATHEMATICAL) mapping Nelfinavir inductive logic programming Virtual networks Function Network operators topology Bandwidth

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Wordification: Propositionalization by unfolding relational data into bags of words

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EXPERT SYSTEMS WITH APPLICATIONS 2015年第17-18期42卷 6442-6456页

作者： Perovsek, Matic Vavpetic, Anze Kranjc, Janez Cestnik, Bojan Lavrac, Nada Jozef Stefan Inst Ljubljana Slovenia Jozef Stefan Int Postgrad Sch Ljubljana Slovenia Temida Doo Ljubljana Slovenia Univ Nova Gorica Nova Gorica Slovenia

inductive logic programming (ILP) and Relational Data Mining (RDM) address the task of inducing models or patterns from multi-relational data. One of the established approaches to RDM is propositionalization, characterized by transforming a relational database into a single-table representation. This paper presents a propositionalization technique called wordification which can be seen as a transformation of a relational database into a corpus of text documents. Wordification constructs simple, easy to understand features, acting as words in the transformed Bag-Of-Words representation. This paper presents the wordification methodology, together with an experimental comparison of several propositionalization approaches on seven relational datasets. The main advantages of the approach are: simple implementation, accuracy comparable to competitive methods, and greater scalability, as it performs several times faster on all experimental databases. Furthermore, the wordification methodology and the evaluation procedure are implemented as executable workflows in the web-based data mining platform ClowdFlows. The implemented workflows include also several other ILP and RDM algorithms, as well as the utility components that were added to the platform to enable access to these techniques to a wider research audience. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Wordification inductive logic programming Relational Data Mining Propositionalization Text mining Classification

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On Progressive Recovery in Interdependent Cyber Physical Systems

On Progressive Recovery in Interdependent Cyber Physical Sys...

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IEEE Global Communications Conference

作者： Yangming Zhao Mohammed Pithapur Chunming Qiao Department of Computer Science and Engineering State University of New York at Buffalo Department of Electrical Engineering State University of New York at Buffalo

ISBN: (纸本)9781509013296

This paper studies how to determine an optimal order of recovering interdependent Cyber Physical Systems (CPS) after a large scale failure. In such a CPS, some failed devices must be repaired first before others can. In addition, such failed devices require a certain amount of repair resources and may take multiple stages to repair. We consider two scenarios: 1) reserved model where all the required repair resources should be prepared at the beginning of repairing a device;and 2) opportunistic model where we can partially repair a device with only part of the required resources. For each scenario, we model it using an Integer Linear programming (ILP) and use a relaxation and rounding method to design an ILP based algorithm. In addition, we also design a Dynamic programming (DP) based algorithm. Simulation results show that ILP based algorithm outperforms DP based algorithm by 10%-20% in systems with less than 200 failed devices, but DP based algorithm can support extreme large size systems with more than 5000 failed devices.

关键词： inductive logic programming algorithms data processing Wound Healing Repair based MULTISTAGE algorithm simulation

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Fast rule mining in ontological knowledge bases with AMIE

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VLDB JOURNAL 2015年第6期24卷 707-730页

作者： Galarraga, Luis Teflioudi, Christina Hose, Katja Suchanek, Fabian M. Telecom ParisTech Paris France Max Planck Inst Informat D-66123 Saarbrucken Germany Aalborg Univ Aalborg Denmark

Recent advances in information extraction have led to huge knowledge bases (KBs), which capture knowledge in a machine-readable format. inductive logic programming (ILP) can be used to mine logical rules from these KBs, such as "If two persons are married, then they (usually) live in the same city." While ILP is a mature field, mining logical rules from KBs is difficult, because KBs make an open-world assumption. This means that absent information cannot be taken as counterexamples. Our approach AMIE (Galarraga et al. in WWW, 2013) has shown how rules can be mined effectively from KBs even in the absence of counterexamples. In this paper, we show how this approach can be optimized to mine even larger KBs with more than 12M statements. Extensive experiments show how our new approach, AMIE, extends to areas of mining that were previously beyond reach.

关键词： Rule mining inductive logic programming ILP Knowledge bases

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inductive programming Meets the Real World

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COMMUNICATIONS OF THE ACM 2015年第11期58卷 90-99页

作者： Gulwani, Sumit Hernandez-Orallo, Jose Kitzelmann, Emanuel Muggleton, Stephen H. Schmid, Ute Zorn, Benjamin Microsoft Corp Programming By Example Res & Engn Grp Redmond WA 98052 USA Univ Politecn Valencia E-46022 Valencia Spain Adam Josef Cuppers Commercial Coll Ratingen Germany Univ London Imperial Coll Sci Technol & Med Dept Comp London SW7 2AZ England Univ Bamberg Bamberg Germany Microsoft Res RiSE Grp Redmond WA USA

inductive programming can liberate users from performing tedious and repetitive tasks.

关键词： inductive logic programming APPLICATION software END users (Information technology) ELECTRONIC spreadsheets SCRIPTING languages (Computer science) INTELLIGENT tutoring systems

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