Considering the shortcomings of existing network key node identification methods based on multiattribute fusion, which have single evaluation and low decision accuracy, combined with advantages high accuracy TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) algorithm applicability grey relational analysis method incomplete information evaluation, concept relative closen...

Clustering aims at grouping of data into clusters based on the similarity between them. It is the pattern of the data that governs grouping. In this paper, we propose method for clustering that is based on finding closeness between the data series. A novel method referred as Clustering with Closeness factor (CCF) is proposed that works in two phases and is not pre-bound with clusters numbers. T...

9 This article proposes an approach to handle multi-attribute decision making (MADM) 10 problems under the interval-valued intuitionistic fuzzy environment, in which both 11 assessments of alternatives on attributes (hereafter, referred to as attribute values) and 12 attribute weights are provided as interval-valued intuitionistic fuzzy numbers (IVIFNs). 13 The notion of relative closeness is e...

In this paper we propose a general approach to find the closest targets for a given unit according to a previously specified criterion of similarity. The idea behind this approach is that inefficient units can more easily learn from those that are more similar and, in addition, closer targets may show for the inefficient units how to achieve the efficiency with less effort. Similarity can be in...

Kadison and Kastler introduced a metric on the set of all C∗-algebras on a fixed Hilbert space. In this paper structural properties of C∗-algebras which are close in this metric are examined. Our main result is that the property of having a positive answer to Kadison’s similarity problem transfers to close C∗-algebras. In establishing this result we answer questions about closeness of commutant...

We present here system report for our model submitted for shared task on Computational Linguistic Scientific-document Summarization (CL-SciSumm) 2017. We hypothesize that search and retrieval based techniques are sub-optimal for learning complex relation likes provenance. State-of-the-art information retrieval techniques using term frequency inverted document frequency (TF-IDF) to capture surfa...

Databases, particularly when storing heterogeneous, sparse semistructured data, tend to provide incomplete information and information which is difficult to categorize. This paper first considers how to classify entity instances as members of entity classes organized in a lattice-like generalization/specialization hierarchy. Then, it describes how the frame representation employed for instances...