Recently, Hua et al. defined a new topological index based on degrees and inverse of distances between all pairs of vertices. They named this new graph invariant as reciprocal degree distance as 1 { , } ( ) ( ( ) ( ))[ ( , )] RDD(G) = u v V G d u  d v d u v , where the d(u,v) denotes the distance between vertices u and v. In this paper, we compute this topological index for Grassmann graphs.

When choosing a portfolio of projects with a multi-attribute weighting model, it is necessary to elicit trade-off statements about how important these attributes are relative to each other. Such statements correspond to weight constraints, and thus impact on which project portfolios are potentially optimal or non-dominated in view of the resulting set of feasible attribute weights. In this pape...

Decisions are an important part of Concurrent Engineering and engineering design in general. Accordingly, more attention should be paid to the means and methods for making these decisions. In this article, a utility-based decision support method for the selection of an engineering design is presented. The utility-based selection decision support problem (u-sDSP) is a synthesized construct that ...

This paper presents a new procedure for fitting multiple geometric structures without having a priori knowledge of scale. Our method leverages on Consensus Clustering, a single-term model selection strategy relying on the principle of stability, thereby avoiding the explicit tradeoff between data fidelity (i.e., modeling error) and model complexity. In particular we tailored this model selectio...

Identification of relevant product attributes is critical to the success of any marketing campaign. This task can be conceptualized as an attribute recommendation problem based on the product’s content or features, where the goal of a solution would be to automatically recommend relevant features to the marketer for highlighting in a campaign. In this research, we try to solve this problem by u...

Abstract In order to better improve students’ Japanese language performance and help them progress, this paper proposes an analysis of personalized teaching in a big data technology environment. We build model learner characteristics use collaborative filtering techniques push learning information from learners with the same or similar interest preference characteristics. Adjust strategies base...

This paper proposes a decision support system which integrates the objective weights of importance of the attributes as well as the subjective preferences of the decision maker to decide the composite weights of importance of the attributes. Using fuzzy set theory the qualitative attributes are converted into the quantitative attributes. Based on this model, a decision support system AGVSEL is ...

Introduction. Real-world networks often consist of nodes with informative attributes as well as links. To properly model these networks, it is necessary to learn how attributes of the nodes relate to the connectivity structure. Metric learning is a natural framework for transforming the raw node features to match the structural properties of a graph. Traditional metric learning algorithms prima...

While decision theory provides an appealing normative framework for representing rich preference structures, eliciting utility or value functions typically incurs a large cost. For many applications involving interactive sys­ tems this overhead precludes the use of for­ mal decision-theoretic models of preference. Instead of performing elicitation in a vacuum, it would be useful if we could aug...