We present a novel methodology for the analysis of activities engaged in an organization such as the research conducted in a University department by mapping them to a related hierarchical taxonomy such as Classification of Computer Subjects by ACM (ACM-CCS). We start by collecting data of activities of the individual components of the organization and present them as the components fuzzy membe...

This paper describes an unsupervised algorithm for placing unknown words into a taxonomy and evaluates its accuracy on a large and varied sample of words. The algorithm works by first using a large corpus to find semantic neighbors of the unknown word, which we accomplish by combining latent semantic analysis with part-of-speech information. We then place the unknown word in the part of the tax...

Recent advances in graph-based search techniques derived from Kleinberg’s work [1] have been impressive. This paper further improves the graph-based search algorithm in two dimensions. Firstly, variants of Kleinberg’s techniques do not take into account the semantics of the query string nor of the nodes being searched. As a result, polysemy of query words cannot be resolved. This paper presents...

routing in ad-hoc networks, specifically intelligent-based ones, is a highly interested research topic in recent years. most of them are simulation-based study. large percentages have not even mentioned some of the fundamental parameters. this strictly reduces their validity and reliability. on the other hand, there is not a comprehensive framework to classify routing algorithms in wireless sen...

In this paper we present a classification of parallel branch and bound algorithms, and elaborate on the consequences of particular parameter settings. The taxonomy is based upon how the algorithms handle the knowledge about the problem instance to be solved, generated during execution. The starting point of the taxonomy is the generally accepted description of the sequential branch and bound al...

In this paper, we present ContrastMedium, an algorithm that transforms noisy semantic networks into full-fledged, clean taxonomies. ContrastMedium is able to identify the embedded taxonomy structure from a noisy knowledge graph without explicit human supervision such as, for instance, a set of manually selected input root and leaf concepts. This is achieved by leveraging structural information ...

Computer scientists are expected to be problem solvers, yet the current structure of algorithm education does not facilitate learning the necessary skills to do so. Learning objectives for algorithm education are defined and Bloom and SOLO taxonomy are employed to evaluate their complexity. Current algorithm curriculum, like that of Michigan State University, is examined and evaluated for e↵ect...

One of the core services provided by description logic (DL) reasoners is classification: determining the subsumption quasi-ordering over the concept names occurring in a knowledge base (KB) and caching this information in the form of a directed acyclic graph known as the concept hierarchy or taxonomy. For less expressive DLs, such as members of the EL family, it may be possible to derive all th...