João Paulo Carvalho

Rule based fuzzy cognitive maps-qualitative systems dynamics

This paper focuses on the rule based fuzzy cognitive maps (RB-FCM) potential to model the dynamics of qualitative real-world systems that include feedback links. It presents a general overview of RB-FCM and proposes a set of possible concepts and relations. It also provides guidelines to introduce time as an important qualitative entity of cognitive maps.

Rule based fuzzy cognitive maps and fuzzy cognitive maps-a comparative study

This paper focuses on the comparison between rule based cognitive maps and fuzzy cognitive maps. The paper shows FCM limitations to represent non-monotonic non-symmetric causal relations, presents results that exhibit the stability of RBFCM in systems where FCM is not stable due to its non-fuzzy inherent nature and presents RBFCM potential to model qualitative real-world dynamic systems.

On the semantics and the use of fuzzy cognitive maps and dynamic cognitive maps in social sciences

Fuzzy cognitive maps (FCMs) were introduced as a tool to model the dynamics of qualitative systems and have been around for more than 20 years. However, how they have been used and the interpretations of their results are nowadays far from their original intended goal. This paper focuses on discussing the structure, the semantics and the possible use of FCM as tools to model and simulate complex social, economic and political systems, while clarifying some issues that have been recurrent in published FCM papers and reviewing some alternative approaches.

Finding top-k elements in data streams

Identifying the most frequent elements in a data stream is a well known and difficult problem. Identifying the most frequent elements for each individual, especially in very large populations, is even harder. The use of fast and small memory footprint algorithms is paramount when the number of individuals is very large. In many situations such analysis needs to be performed and kept up to date in near real time. Fortunately, approximate answers are usually adequate when dealing with this problem. This paper presents a new and innovative algorithm that addresses this problem by merging the commonly used counter-based and sketch-based techniques for top-k identification. The algorithm provides the top-k list of elements, their frequency and an error estimate for each frequency value. It also provides strong guarantees on the error estimate, order of elements and inclusion of elements in the list depending on their real frequency. Additionally the algorithm provides stochastic bounds on the error and expected error estimates. Telecommunications customers behavior and voice call data is used to present concrete results obtained with this algorithm and to illustrate improvements over previously existing algorithms.

Authorship identification and author fuzzy “fingerprints”

Fingerprint identification is a well-known technique in forensic sciences. The basic idea of identifying a subject based on a set of features left by the subject actions or behavior can be applied to other domains. Identifying text authorship based on an author “fingerprint” is one such application. This paper considers the problem of extracting “fingerprints” from texts and matching them with those obtained from a set of known authors. It presents an innovative fuzzy fingerprint algorithm based on vector valued fuzzy sets. Words and other stylometric features are used to create the fingerprint. The implementation is based on an approximated fast and compact algorithm that allows the method to be used on near real time, even for a large number of authors and texts.

Qualitative optimization of Fuzzy Causal Rule Bases using Fuzzy Boolean Nets

Fuzzy Causal Rule Bases (FCRb) are widely used and are the most important rule bases in Rule Based Fuzzy Cognitive Maps (RB-FCM). However, FCRb are subject to several restrictions that create difficulties in their creation and completion. This paper proposes a method to optimally complete FCRb using Fuzzy Boolean Net properties as qualitative universal approximators. Although the proposed approach focuses on FCRb, it can be generalized to any fuzzy rule base.

Issues on the stability of fuzzy cognitive maps and rule-based fuzzy cognitive maps

This paper focuses on several stability issues regarding the modeling of the dynamics of qualitative real world systems, and the ability of fuzzy cognitive maps and rule-based fuzzy cognitive maps to provide a faithful modeling in what concerns the stability properties of those systems. It also introduces the concept of intrinsic stability as a necessary property of qualitative system dynamics modeling tools.

Twitter Topic Fuzzy Fingerprints

In this paper we propose to approach the subject of Twitter Topic Detection using a new technique called Topic Fuzzy Fingerprints. A comparison is made with two popular text classification techniques, Support Vector Machines (SVM) and fc-Nearest Neighbours (fcNN). Preliminary results show that Twitter Topic Fuzzy Fingerprints outperforms the other two techniques achieving better Precision and Recall, while still being much faster, which is an essential feature when processing large volumes of streaming data.

Finding top-k elements in a time-sliding window

Identifying the top-k most frequent elements is one of the many problems associated with data streams analysis. It is a well-known and difficult problem, especially if the analysis is to be performed and maintained up to date in near real time. Analyzing data streams in time sliding window model is of particular interest as only the most recent, more relevant events are considered. Approximate answers are usually adequate when dealing with this problem. This paper presents a new and innovative algorithm, the Filtered Space-Saving with Sliding Window Algorithm (FSW) that addresses this problem by introducing in the Filtered Space Saving (FSS) algorithm an approximated time sliding window counter. The algorithm provides the top-k list of elements, their frequency and an error estimate for each frequency value within the sliding window. It provides strong guarantees on the results, depending on the elements real frequencies. Experimental results detail performance on real life cases.

Forest Fire Modelling using Rule-Based Fuzzy Cognitive Maps and Voronoi Based Cellular Automata

This paper focus on the modelling and simulation of forest fire propagation using dynamic cognitive map cellular automata, where rule based fuzzy cognitive maps are used to represent the evolution of burning areas in Voronoi region based cells