| 1. |
- Abril, Daniel, et al.
(författare)
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Supervised Learning Using a Symmetric Bilinear Form for Record Linkage
- 2015
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Ingår i: Information Fusion. - : Elsevier. - 1566-2535 .- 1872-6305. ; 26, s. 144-153
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Tidskriftsartikel (refereegranskat)abstract
- Record Linkage is used to link records of two different files corresponding to the same individuals. These algorithms are used for database integration. In data privacy, these algorithms are used to evaluate the disclosure risk of a protected data set by linking records that belong to the same individual. The degree of success when linking the original (unprotected data) with the protected data gives an estimation of the disclosure risk.In this paper we propose a new parameterized aggregation operator and a supervised learning method for disclosure risk assessment. The parameterized operator is a symmetric bilinear form and the supervised learning method is formalized as an optimization problem. The target of the optimization problem is to find the values of the aggregation parameters that maximize the number of re-identification (or correct links). We evaluate and compare our proposal with other non-parametrized variations of record linkage, such as those using the Mahalanobis distance and the Euclidean distance (one of the most used approaches for this purpose). Additionally, we also compare it with other previously presented parameterized aggregation operators for record linkage such as the weighted mean and the Choquet integral. From these comparisons we show how the proposed aggregation operator is able to overcome or at least achieve similar results than the other parameterized operators. We also study which are the necessary optimization problem conditions to consider the described aggregation functions as metric functions.
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| 2. |
- Alcantud, Jose Carlos R., et al.
(författare)
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Decomposition theorems and extension principles for hesitant fuzzy sets
- 2018
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Ingår i: Information Fusion. - : Elsevier. - 1566-2535 .- 1872-6305. ; 41, s. 48-56
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Tidskriftsartikel (refereegranskat)abstract
- We prove a decomposition theorem for hesitant fuzzy sets, which states that every typical hesitant fuzzy set on a set can be represented by a well-structured family of fuzzy sets on that set. This decomposition is expressed by the novel concept of hesitant fuzzy set associated with a family of hesitant fuzzy sets, in terms of newly defined families of their cuts. Our result supposes the first representation theorem of hesitant fuzzy sets in the literature. Other related representation results are proven. We also define two novel extension principles that extend crisp functions to functions that map hesitant fuzzy sets into hesitant fuzzy sets.
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| 3. |
- Bouguelia, Mohamed-Rafik, 1987-, et al.
(författare)
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Mode tracking using multiple data streams
- 2018
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Ingår i: Information Fusion. - Amsterdam : Elsevier BV. - 1566-2535 .- 1872-6305. ; 43, s. 33-46
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Tidskriftsartikel (refereegranskat)abstract
- Most existing work in information fusion focuses on combining information with well-defined meaning towards a concrete, pre-specified goal. In contradistinction, we instead aim for autonomous discovery of high-level knowledge from ubiquitous data streams. This paper introduces a method for recognition and tracking of hidden conceptual modes, which are essential to fully understand the operation of complex environments, and an important step towards building truly intelligent aware systems. We consider a scenario of analyzing usage of a fleet of city buses, where the objective is to automatically discover and track modes such as highway route, heavy traffic, or aggressive driver, based on available on-board signals. The method we propose is based on aggregating the data over time, since the high-level modes are only apparent in the longer perspective. We search through different features and subsets of the data, and identify those that lead to good clusterings, interpreting those clusters as initial, rough models of the prospective modes. We utilize Bayesian tracking in order to continuously improve the parameters of those models, based on the new data, while at the same time following how the modes evolve over time. Experiments with artificial data of varying degrees of complexity, as well as on real-world datasets, prove the effectiveness of the proposed method in accurately discovering the modes and in identifying which one best explains the current observations from multiple data streams.
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| 4. |
- Diez-Olivan, Alberto, et al.
(författare)
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Data Fusion and Machine Learning for Industrial Prognosis : Trends and Perspectives towards Industry 4.0
- 2018
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Ingår i: Information Fusion. - : Elsevier. - 1566-2535 .- 1872-6305. ; 50, s. 92-111
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Tidskriftsartikel (refereegranskat)abstract
- The so-called “smartization” of manufacturing industries has been conceived as the fourth industrial revolution or Industry 4.0, a paradigm shift propelled by the upsurge and progressive maturity of new Information and Communication Technologies (ICT) applied to industrial processes and products. From a data science perspective, this paradigm shift allows extracting relevant knowledge from monitored assets through the adoption of intelligent monitoring and data fusion strategies, as well as by the application of machine learning and optimization methods. One of the main goals of data science in this context is to effectively predict abnormal behaviors in industrial machinery, tools and processes so as to anticipate critical events and damage, eventually causing important economical losses and safety issues. In this context, data-driven prognosis is gradually gaining attention in different industrial sectors. This paper provides a comprehensive survey of the recent developments in data fusion and machine learning for industrial prognosis, placing an emphasis on the identification of research trends, niches of opportunity and unexplored challenges. To this end, a principled categorization of the utilized feature extraction techniques and machine learning methods will be provided on the basis of its intended purpose: analyze what caused the failure (descriptive), determine when the monitored asset will fail (predictive) or decide what to do so as to minimize its impact on the industry at hand (prescriptive). This threefold analysis, along with a discussion on its hardware and software implications, intends to serve as a stepping stone for future researchers and practitioners to join the community investigating on this vibrant field.
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| 5. |
- Krish, Ram P., et al.
(författare)
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Improving Automated Latent Fingerprint Identification Using Extended Minutia Types
- 2019
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Ingår i: Information Fusion. - Amsterdam : Elsevier. - 1566-2535 .- 1872-6305. ; 50, s. 9-19
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Tidskriftsartikel (refereegranskat)abstract
- Latent fingerprints are usually processed with Automated Fingerprint Identification Systems (AFIS) by law enforcement agencies to narrow down possible suspects from a criminal database. AFIS do not commonly use all discriminatory features available in fingerprints but typically use only some types of features automatically extracted by a feature extraction algorithm. In this work, we explore ways to improve rank identification accuracies of AFIS when only a partial latent fingerprint is available. Towards solving this challenge, we propose a method that exploits extended fingerprint features (unusual/rare minutiae) not commonly considered in AFIS. This new method can be combined with any existing minutiae-based matcher. We first compute a similarity score based on least squares between latent and tenprint minutiae points, with rare minutiae features as reference points. Then the similarity score of the reference minutiae-based matcher at hand is modified based on a fitting error from the least square similarity stage. We use a realistic forensic fingerprint casework database in our experiments which contains rare minutiae features obtained from Guardia Civil, the Spanish law enforcement agency. Experiments are conducted using three minutiae-based matchers as a reference, namely: NIST-Bozorth3, VeriFinger-SDK and MCC-SDK. We report significant improvements in the rank identification accuracies when these minutiae matchers are augmented with our proposed algorithm based on rare minutiae features. © 2018 Elsevier B.V.
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| 6. |
- Praveen Kumar, D., et al.
(författare)
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Machine learning algorithms for wireless sensor networks: A survey
- 2019
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Ingår i: Information Fusion. - : Elsevier BV. - 1566-2535 .- 1872-6305. ; 49, s. 1-25
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Tidskriftsartikel (refereegranskat)abstract
- Wireless sensor network (WSN) is one of the most promising technologies for some real-time applications because of its size, cost-effective and easily deployable nature. Due to some external or internal factors, WSN may change dynamically and therefore it requires depreciating dispensable redesign of the network. The traditional WSN approaches have been explicitly programmed which make the networks hard to respond dynamically. To overcome such scenarios, machine learning (ML) techniques can be applied to react accordingly. ML is the process of self-learning from the experiences and acts without human intervention or re-program. The survey of the ML techniques for WSNs is presented in [1], covering period of 2002–2013. In this survey, we present various ML-based algorithms for WSNs with their advantages, drawbacks, and parameters effecting the network lifetime, covering the period from 2014–March 2018. In addition, we also discuss ML algorithms for synchronization, congestion control, mobile sink scheduling and energy harvesting. Finally, we present a statistical analysis of the survey, the reasons for selection of a particular ML techniques to address an issue in WSNs followed by some discussion on the open issues.
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| 7. |
- Rodríguez, R. M., et al.
(författare)
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A Position and Perspective Analysis of Hesitant Fuzzy Sets on Information Fusion in Decision Making : Towards High Quality Progress
- 2016
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Ingår i: Information Fusion. - : Elsevier. - 1566-2535 .- 1872-6305. ; 29, s. 89-97
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Tidskriftsartikel (refereegranskat)abstract
- The necessity of dealing with uncertainty in real world problems has been a long-term research challenge which has originated different methodologies and theories. Recently, the concept of Hesitant Fuzzy Sets (HFSs) has been introduced to model the uncertainty that often appears when it is necessary to establish the membership degree of an element and there are some possible values that make to hesitate about which one would be the right one. Many researchers have paid attention on this concept who have proposed diverse extensions, relationships with other types of fuzzy sets, different types of operators to compute with this type of information, applications on information fusion and decision-making, etc.Nevertheless, some of these proposals are questionable, because they are straightforward extensions of previous works or they do not use the concept of HFSs in a suitable way. Therefore, this position paper studies the necessity of HFSs and provides a discussion about current proposals including a guideline that the proposals should follow and some challenges of HFSs.
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| 8. |
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| 9. |
- Torra, Vicenç, et al.
(författare)
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Maximal c consensus meets
- 2019
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Ingår i: Information Fusion. - NETHERLANDS : Elsevier. - 1566-2535 .- 1872-6305. ; 51, s. 58-66
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Tidskriftsartikel (refereegranskat)abstract
- Given a set S of subsets of a reference set X, we define the problem of finding c subsets of X that maximize the size of the intersection among the included subsets. Maximizing the size of the intersection means that they are subsets of the sets in S and they are as large as possible. We can understand the result of this problem as c consensus sets of S, or c consensus representatives of S. From the perspective of lattice theory, each representative will be a meet of some sets in S. In this paper we define formally this problem, and present heuristic algorithms to solve it. We also discuss the relationship with other established problems in the literature.
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| 10. |
- Torra, Vicenç, et al.
(författare)
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Numerical integration for the Choquet integral
- 2016
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Ingår i: Information Fusion. - : Elsevier. - 1566-2535 .- 1872-6305. ; 31, s. 137-145
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Tidskriftsartikel (refereegranskat)abstract
- Choquet integrals with respect to non-additive (or fuzzy measures) have been used in a large number of applications because they permit us to integrate information from different sources when there are interactions. Successful applications use a discrete reference set. In the case of measures on a continuous reference set, as e.g. the real line, few results have been obtained that permit us to have an analytical expression of the integral. However, in most of the cases there is no such analytical expression. In this paper we describe how to perform the numerical integration of a Choquet integral with respect to a non-additive measure.
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