Evidential Label Propagation Algorithm for Graphs

Community detection has attracted considerable attention crossing many areas as it can be used for discovering the structure and features of complex networks. With the increasing size of social networks in real world, community detection approaches should be fast and accurate. The Label Propagation Algorithm (LPA) is known to be one of the near-linear solutions and benefits of easy implementation, thus it forms a good basis for efficient community detection methods. In this paper, we extend the update rule and propagation criterion of LPA in the framework of belief functions. A new community detection approach, called Evidential Label Propagation (ELP), is proposed as an enhanced version of conventional LPA. The node influence is first defined to guide the propagation process. The plausibility is used to determine the domain label of each node. The update order of nodes is discussed to improve the robustness of the method. ELP algorithm will converge after the domain labels of all the nodes become unchanged. The mass assignments are calculated finally as memberships of nodes. The overlapping nodes and outliers can be detected simultaneously through the proposed method. The experimental results demonstrate the effectiveness of ELP.Comment: 19th International Conference on Information Fusion, Jul 2016, Heidelber, Franc

Interaction Analysis in Smart Work Environments through Fuzzy Temporal Logic

Interaction analysis is defined as the generation of situation descriptions from machine perception. World models created through machine perception are used by a reasoning engine based on fuzzy metric temporal logic and situation graph trees, with optional parameter learning and clustering as preprocessing, to deduce knowledge about the observed scene. The system is evaluated in a case study on automatic behavior report generation for staff training purposes in crisis response control rooms

08421 Abstracts Collection -- Uncertainty Management in Information Systems

From October 12 to 17, 2008 the Dagstuhl Seminar 08421 \u27`Uncertainty Management in Information Systems \u27\u27 was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. The abstracts of the plenary and session talks given during the seminar as well as those of the shown demos are put together in this paper

Interaction Analysis in Smart Work Environments through Fuzzy Temporal Logic

Interaction analysis is defined as the generation of situation descriptions from machine perception. World models created through machine perception are used by a reasoning engine based on fuzzy metric temporal logic and situation graph trees, with optional parameter learning and clustering as preprocessing, to deduce knowledge about the observed scene. The system is evaluated in a case study on automatic behavior report generation for staff training purposes in crisis response control rooms

Web Shopping Expert Systems Using New Interval Type-2 Fuzzy Reasoning

Finding a product with high quality and reasonable price online is a difficult task due to the fuzzy nature of data and queries. In order to handle the fuzzy problem, a new type-2 fuzzy reasoning based decision support system, the Web Shopping Expert for online users is proposed. In the Web Shopping Expert, an interval type-2 fuzzy logic system is used and a fuzzy output can be obtained using the up-low limit technique, which offers an opportunity to directly employ all the rules and methods of the type-1 fuzzy sets onto the type-2 fuzzy sets. To achieve the best performance the fuzzy inference system is optimized by the least square and numerical method. The key advantages of the least square method are the efficient use of samples and the simplicity of the implementation. The Web Shopping Expert based on the interval type-2 fuzzy inference system provides more reasonable conclusions for online users

From fuzzy to annotated semantic web languages

The aim of this chapter is to present a detailed, selfcontained and comprehensive account of the state of the art in representing and reasoning with fuzzy knowledge in Semantic Web Languages such as triple languages RDF/RDFS, conceptual languages of the OWL 2 family and rule languages. We further show how one may generalise them to so-called annotation domains, that cover also e.g. temporal and provenance extensions

A decision support model for differential sticking avoidance

An innovative theoretical model to quantify the risk of differential sticking is presented. The proposed risk assessment is based on the concept of likelihood versus consequence. The likelihood of the problem’s occurrence in a given wellbore segment (case) is evaluated from a knowledge-based model and translated by a similarity measure of relevant operational conditions between the target case and historical cases with known outcomes. The stand alone module performed satisfactorily and predicts the likelihood of occurrence by more than a chance probability, demonstrated by a rate of sixty eight percent (68%) correct predictions against field data from forty four wells drilled by different operators in several fields.The consequence assessment is performed through an unidimensional mechanistic model that predicts the downhole overpull (differential sticking force) and performed well while estimating reported overpulls from known field instances of the problem. Together, the models serve as a risk assessment tool able to correctly describe risk operational trends while designing or drilling wells, with critical situations being defined as high likelihood plus high potential overpulls. Both models utilizes unique experimental data about mechanical properties of drilling fluids filtercakes (hardness, torque resistance and adhesion-cohesion strength) under simulated downhole conditions, raised through the HTHP Mudcake Characterization Equipment developed during the course of this research work. Moreover, the study contributes towards the development of modern predictive models aiming at combining large amount of available operational drilling data (LWD, PWD, mudlogging, survey, drilling reports, etc), expert’s knowledge, laboratory data and phenomenological models in order to optimize drilling operations