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science and Information Conference (SAI)

作者： Elnaz Bigdeli Bijan Raahemi Mahdi Mohammadi Stan Matwin School of Electrical Engineering and Computer Science University of Ottawa Ottawa ON Canada Telfer School of Management Knowledge Discovery and Data Mining lab University of Ottawa E. Ottawa ON Canada Department of Computing Dalhousie University Halifax NB Canada Polish Academy of Sciences Warsaw Poland

Anomaly detection algorithms face several challenges including computational complexity and resiliency to noise in input data. In this paper, we propose a fast and noise-resilient cluster-based anomaly detection method using collective labelling approach. In the proposed Collective Probabilistic Anomaly Detection method, first instead of labelling each new sample (as normal or anomaly) individually, the new samples are clustered, then labelled. This collective labelling mitigates the negative impact of noise by relying on group behaviour rather than individual characteristics of incoming samples. Second, since grouping and labelling new samples may be time-consuming, we summarize clusters using Gaussian Mixture Model (GMM). Not only does GMM offer faster processing speed; it also facilitates summarizing clusters with arbitrary shape, and consequently, reducing the memory space requirement. Finally, a modified distance measure, based on Kullback-Liebner method, is proposed to calculate the similarity among clusters represented by GMMs. We evaluate the proposed method on various datasets by measuring its false alarm rate, detection rate and memory requirement. We also add different levels of noise to the input datasets to demonstrate the performance of the proposed collective anomaly detection method in the presence of noise. The experimental results confirm superior performance of the proposed method compared to individually-based labelling techniques in terms of memory usage, detection rate and false alarm rate.

关键词： Noise Shape Training Gaussian mixture model Clustering algorithms Support vector machines

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Footprint Recognition with Principal Component Analysis and Independent Component Analysis

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Macromolecular Symposia 2015年第1期347卷

作者： Rohit Khokher Ram Chandra Singh Rahul Kumar Department of Computer Science and Engineering Vidya College of Engineering Vidya Knowledge Park Meerut 250005 India Department of Physics Vidya College of Engineering Vidya Knowledge Park Meerut 250005 India Department of Computer Science and Engineering School of Engineering and Technology Sharda University Knowledge Park III Greater Noida 201306 India

The finger print recognition, face recognition, hand geometry, iris recognition, voice scan, signature, retina scan and several other biometric patterns are being used for recognition of an individual. Human footprint is one of the relatively new physiological biometrics due to its stable and unique characteristics. The texture and foot shape information of footprint offers one of the powerful means in personal recognition. This work proposes a footprint based biometric identification of an individual by extracting texture and shape based features using Principal Component Analysis (PCA) and Independent Component Analysis (ICA) linear projection techniques. PCA is a commonly used technique for data classification and dimensionality reduction and ICA is one of the most widely used blind source separation technique for revealing hidden factors that underlie sets of random variables, measurements, or signals. In this study PCA and ICA have been compared for footprint recognition using distance classification techniques such as Euclidean distance, city block, cosine and correlation. Experimental results show that ICA performs better than PCA for footprint recognition.

关键词： biometrics distance algorithms footprint recognition independent component analysis principal component analysis

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Geometric intuition and algorithms for Ev-SVM

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2015年第1期16卷

作者： Àlvaro Barbero Akiko Takeda Jorge López Department of Computer Science and Knowledge-Engineering Institute Autonomous University of Madrid Madrid Spain Department of Mathematical Informatics The University of Tokyo Tokyo Japan Department of Computer Science and Knowledge-Engineering Institute Autonomous University of Madrid Madrid Spain

In this work we address the Ev-SVM model proposed by Pérez-Cruz et al. as an extension of the traditional v support vector classification model (v-SVM). Through an enhancement of the range of admissible values for the regularization parameter v, the Ev-SVM has been shown to be able to produce a wider variety of decision functions, giving rise to a better adaptability to the data. However, while a clear and intuitive geometric interpretation can be given for the v-SVM model as a nearest-point problem in reduced convex hulls (RCH-NPP), no previous work has been made in developing such intuition for the Ev-SVM model. In this paper we show how Ev-SVM can be reformulated as a geometrical problem that generalizes RCH-NPP, providing new insights into this model. Under this novel point of view, we propose the RapMinos algorithm, able to solve Ev-SVM more efficiently than the current methods. Furthermore, we show how RapMinos is able to address the Ev-SVM model for any choice of regularization norm lp ≥1 seamlessly, which further extends the SVM model flexibility beyond the usual Ev-SVM models.

关键词： Ev-SVM SVM classification nearest point problem reduced convex hulls

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Airport context analytics

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8741卷 179-184页

作者： Katsiri, Eli Papastefanatos, George Terrovitis, Manolis Sellis, Timos Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi67100 Greece Institute for the Management of Information Systems Research and Innovation Centre in Information Communication and Knowledge Technologies - "Athena" Artemidos 6 & Epidaurou Marousi Athens15125 Greece School of Computer Science and Information Technology RMIT University Australia

Underpinning the above vision is the ability to target service content to users’ current context, e.g., their location, intent, environment, in real time. The contribution of this work is that it uses a pervasive computing system with three key ingredients: (a) a data model, comprising user and service content entities, (b) a user context model and (c) rules for simple pattern matching on service content and user context event streams. This modus operandi is encapsulated inside a SOA architecture, the Common Airport Portal - CAP and it is illustrated through the description of a real application, Offers and Coupons Services that was deployed recently at Athens International Airport (AIA) (http://***).Airports today can constitute a perfect environment for developing novel digital marketplaces offering location-specific and semantically rich context-aware services, such as personalized marketing campaigns, last minute, discounted airline tickets while helping users access the airport and speed through the airport process. © Springer International Publishing Switzerland 2014.

关键词： Information services

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Attenuation of signal at a tropical location with radiosonde data due to cloud

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International Journal of Smart Home 2014年第1期8卷 15-22页

作者： Mandal, Bijoy Kumar Bhattacharyya, Debnath Kang, Sungmin Computer Science and Engineering Department FET NSHM Knowledge Campus - Durgapur Durgapur-713212 India School of Business Administration College of Business and Economics Chung-Ang University 84 Heukseok-ro Dongjak-gu Seoul 156-861 Korea Republic of

Cloud attenuation is calculated from cloud liquid water content (LWC). Cloud liquid water content (LWC) is derived from the radiosonde data using the Salonen model, show a prominent linear variation with the attenuation contribution due to cloud at a tropical location. In this paper, the attenuation contribution due to cloud liquid water content (LWC) and attenuation contribution due to cloud ice water content is studied at different frequencies in the tropical region. Cloud liquid water content shows a greater contribution compared to Cloud ice water content in causing attenuation of signal due to cloud in troposphere. ©2014 SERSC.

关键词： Liquids

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Monte Carlo Tree Search with heuristic evaluations using implicit minimax backups

Monte Carlo Tree Search with heuristic evaluations using imp...

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IEEE Symposium on Computational Intelligence and Games, CIG

作者： Marc Lanctot Mark H. M. Winands Tom Pepels Nathan R. Sturtevant Department of Knowledge Engineering Maastricht University Computer Science Department University of Denver

Monte Carlo Tree Search (MCTS) has improved the performance of game engines in domains such as Go, Hex, and general game playing. MCTS has been shown to outperform classic αβ search in games where good heuristic evaluations are difficult to obtain. In recent years, combining ideas from traditional minimax search in MCTS has been shown to be advantageous in some domains, such as Lines of Action, Amazons, and Breakthrough. In this paper, we propose a new way to use heuristic evaluations to guide the MCTS search by storing the two sources of information, estimated win rates and heuristic evaluations, separately. Rather than using the heuristic evaluations to replace the playouts, our technique backs them up implicitly during the MCTS simulations. These minimax values are then used to guide future simulations. We show that using implicit minimax backups leads to stronger play performance in Kalah, Breakthrough, and Lines of Action.

关键词： Games Silicon

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Clustering citation distributions for semantic categorization and citation prediction 4

Clustering citation distributions for semantic categorizatio...

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4th Workshop on Linked science: Making Sense Out of Data, LISC 2014, Collocated with the 13th International Semantic Web Conference, ISWC 2014

作者： Osborne, Francesco Peroni, Silvio Motta, Enrico Knowledge Media Institute Open University Milton Keynes United Kingdom Department of Computer Science and Engineering University of Bologna Bologna Italy STLab CNR Institute of Cognitive Sciences and Technologies Rome Italy

In this paper we present i) an approach for clustering authors according to their citation distributions and ii) an ontology, the Bibliometric Data Ontology, for supporting the formal representation of such clusters. This method allows the formulation of queries which take in consideration the citation behaviour of an author and predicts with a good level of accuracy future citation behaviours. We evaluate our approach with respect to alternative solutions and discuss the predicting abilities of the identified clusters.

关键词： Data mining

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Maestra at LifeCLEF 2014 plant task: Plant identification using visual data

Maestra at LifeCLEF 2014 plant task: Plant identification us...

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2014 Cross Language Evaluation Forum Conference, CLEF 2014

作者： Dimitrovski, Ivica Madjarov, Gjorgji Lameski, Petre Kocev, Dragi Faculty of Computer Science and Engineering University of Ss Cyril and Methodius Rugjer Boshkovikj 16 Skopje1000 Macedonia Department of Knowledge Technologies Jožef Stefan Institute Jamova 39 Ljubljana1000 Slovenia

In this paper, we describe an approach to the automatic plant identification task of the LifeCLEF 2014 lab. The image descriptors for all submitted runs were obtained using the bag-of-visual-words method. For the leaf scans, we use multiscale triangular shape descriptor and for the other plant organs Opponent SIFT extracted around points of interest obtained using Harris-Laplace detector. We then use approximate κ-means (AKM) algorithm to cluster these descriptors in large number of clusters/visual words (approximately 200K). Each image in the training and test dataset is represented as a sparse high-dimensional histogram of term (visual word) occurrences. The similarity between two images is defined as a L2 distance over the obtained histograms. We use the standard tf-idf weighting scheme, which reduces the contribution that commonly occurring, and therefore less discriminative, words make to the similarity. To obtain the predictions, we employ a late fusion scheme for combining the similarities/ranks from multiple ranked image lists build for each type of view. Overall the proposed methods performed well, we ranked fifth, out of 10 competing groups.

关键词： Graphic methods

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Keeping speed and distance for aligned motion

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Physical Review E 2015年第1期91卷 012807-012807页

作者： Illés J. Farkas Jeromos Kun Yi Jin (金祎) Gaoqi He (何高奇) Mingliang Xu (徐明亮) MTA-ELTE Statistical and Biological Physics Research Group (Hungarian Academy of Sciences) Pázmány Péter sétány 1A Budapest 1117 Hungary Regional Knowledge Center ELTE Faculty of Sciences Irányi Dániel u. 4. Székesfehérvár 8000 Hungary Department of Biological Physics Eötvös University Pázmány Péter sétány 1A Budapest 1117 Hungary Department of Computer Science and Engineering East China University of Science and Technology 130 Meilong Road Shanghai 200237 China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing 100191 China School of Information Engineering Zhengzhou University 100 Science Avenue Zhengzhou 450001 China

The cohesive collective motion (flocking, swarming) of autonomous agents is ubiquitously observed and exploited in both natural and man-made settings, thus, minimal models for its description are essential. In a model with continuous space and time we find that if two particles arrive symmetrically in a plane at a large angle, then (i) radial repulsion and (ii) linear self-propelling toward a fixed preferred speed are sufficient for them to depart at a smaller angle. For this local gain of momentum explicit velocity alignment is not necessary, nor are adhesion or attraction, inelasticity or anisotropy of the particles, or nonlinear drag. With many particles obeying these microscopic rules of motion we find that their spatial confinement to a square with periodic boundaries (which is an indirect form of attraction) leads to stable macroscopic ordering. As a function of the strength of added noise we see—at finite system sizes—a critical slowing down close to the order-disorder boundary and a discontinuous transition. After varying the density of particles at constant system size and varying the size of the system with constant particle density we predict that in the infinite system size (or density) limit the hysteresis loop disappears and the transition becomes continuous. We note that animals, humans, drones, etc., tend to move asynchronously and are often more responsive to motion than positions. Thus, for them velocity-based continuous models can provide higher precision than coordinate-based models. An additional characteristic and realistic feature of the model is that convergence to the ordered state is fastest at a finite density, which is in contrast to models applying (discontinuous) explicit velocity alignments and discretized time. To summarize, we find that the investigated model can provide a minimal description of flocking.

关键词： ELECTROSTATIC flocking ANISOTROPY INTELLIGENT agents (computer software) UBIQUITOUS computing DISCRETIZATION methods computer engineering

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Introduction to the "Soft computing and intelligent data analysis" minitrack

Proceedings of the Annual Hawaii International Conference on...

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Proceedings of the Annual Hawaii International Conference on System sciences 2014年 1334-1334页

作者： Kruse, Rudolf Otto von Guericke University Magdeburg Germany Faculty of Computer Science Department of Knowledge Processing and Language Engineering Germany

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