Semantic-driven matchmaking of web services using case-based reasoning

With the rapid proliferation of Web services as the medium of choice to securely publish application services beyond the firewall, the importance of accurate, yet flexible matchmaking of similar services gains importance both for the human user and for dynamic composition engines. In this paper, we present a novel approach that utilizes the case based reasoning methodology for modelling dynamic Web service discovery and matchmaking. Our framework considers Web services execution experiences in the decision making process and is highly adaptable to the service requester constraints. The framework also utilises OWL semantic descriptions extensively for implementing both the components of the CBR engine and the matchmaking profile of the Web services

Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning

Visual question answering requires high-order reasoning about an image, which is a fundamental capability needed by machine systems to follow complex directives. Recently, modular networks have been shown to be an effective framework for performing visual reasoning tasks. While modular networks were initially designed with a degree of model transparency, their performance on complex visual reasoning benchmarks was lacking. Current state-of-the-art approaches do not provide an effective mechanism for understanding the reasoning process. In this paper, we close the performance gap between interpretable models and state-of-the-art visual reasoning methods. We propose a set of visual-reasoning primitives which, when composed, manifest as a model capable of performing complex reasoning tasks in an explicitly-interpretable manner. The fidelity and interpretability of the primitives' outputs enable an unparalleled ability to diagnose the strengths and weaknesses of the resulting model. Critically, we show that these primitives are highly performant, achieving state-of-the-art accuracy of 99.1% on the CLEVR dataset. We also show that our model is able to effectively learn generalized representations when provided a small amount of data containing novel object attributes. Using the CoGenT generalization task, we show more than a 20 percentage point improvement over the current state of the art.Comment: CVPR 2018 pre-prin

Modular termination verification for non-blocking concurrency

© Springer-Verlag Berlin Heidelberg 2016.We present Total-TaDA, a program logic for verifying the total correctness of concurrent programs: that such programs both terminate and produce the correct result. With Total-TaDA, we can specify constraints on a thread’s concurrent environment that are necessary to guarantee termination. This allows us to verify total correctness for nonblocking algorithms, e.g. a counter and a stack. Our specifications can express lock- and wait-freedom. More generally, they can express that one operation cannot impede the progress of another, a new non-blocking property we call non-impedance. Moreover, our approach is modular. We can verify the operations of a module independently, and build up modules on top of each other