Decision Support System (DSS) aims to provide effective support for solving unstructured, ill-structured or wicked problems as its initial emergence in the late 1960s. The ever-lasting complexity which exists in social world brings a great deal of uncertainties in human activities, mainly for decision makers who are in morass of overwhelming flow of data, information and knowledge but still lac...

Web users are increasingly looking for structured data, such as lyrics, job, or recipes, using unstructured queries on the web. However, retrieving relevant results from such data is a challenging problem due to the unstructured language of the web queries. In this paper, we propose a method to improve web search ranking by detecting Structured Annotation of queries based on top search results....

This paper addresses the problem of transforming a process model with an arbitrary topology into an equivalent well-structured process model. While this problem has received significant attention, there is still no full characterization of the class of unstructured process models that can be transformed into well-structured ones, nor an automated method to structure any process model that belon...

RNA is usually classified as either structured or unstructured; however, neither category is adequate in describing the diversity of secondary structures expected in biological systems We describe this diversity within the ensemble of structures by using two different metrics: the average Shannon entropy and the ensemble defect. The average Shannon entropy is a measure of the structural diversi...

We develop closed-form expressions of the expected minimum search energy cost and replication energy cost for both unstructured sensor networks (which use blind sequential search for querying) and structured sensor networks (which use efficient hash-based querying). We use both the square grid and random topology to derive each cost modeling. We find that the search cost of unstructured network...

This paper presents a novel approach to the task of automatically inferring the most probable diagnosis from a given clinical narrative. Structured Knowledge Bases (KBs) can be useful for such complex tasks but not sufficient. Hence, we leverage a vast amount of unstructured free text to integrate with structured KBs. The key innovative ideas include building a concept graph from both structure...

Knowledge management systems (KMS) are increasingly becoming popular and important in managing organizational knowledge. This motivates a closer inspection of the degree of usability of various types of KMS. This paper is an analysis of KMS from a philosophical angle: with the help of veritistic social epistemology we analyze which KMS are likely to be used more in comparison to others. Veritis...

The Web contains a huge amount of text that is currently beyond the reach of structured access tools. This unstructured data often contains a substantial amount of implicit structure, much of which can be captured using information extraction (IE) algorithms. By combining an IE system with an appropriate data model and query language, we could enable structured access to all of the Web’s unstru...

This paper proposes an off-line state-space control methodology for enhancing the robustness of multivariable Model Predictive Control (MPC) through the convex optimization of the Youla parameter. The Youla parameter-based optimization strategy allows convex specifications in closed-loop representation, focusing on the robustification of an initial controller using LMIs (Linear Matrix Inequalit...

We investigate the behavior of eigenvalues under structured perturbations. We show that for many common structures such as (complex) symmetric, Toeplitz, symmetric Toeplitz, circulant and others the structured condition number is equal to the unstructured condition number for normwise perturbations, and prove similar results for real perturbations. An exception are complex skewsymmetric matrice...