Search results for "Rankin"
showing 10 items of 259 documents
Ranking and unrankingk-ary trees with a 4k –4 letter alphabet
1997
Abstract The problem of the direct generation in A-order of binary trees was stated by Zaks in 1980. In 1988 Roelants van Baronaigien and Ruskey gave a solution for k-ary trees with n internal nodes using an encoding sequence of kn+1 integers between 1 and n. Vajnovszki and Pallo improved this result for binary trees in 1994 using words of length n–1 on a four letter alphabet. Recently Korsh generalized the Vajnovszki and Pallo’s generating algorithm to k-ary trees using an alphabet whose cardinality depends on k but not on n. We give in this paper ranking and unranking algorithms for k-ary trees using the Korsh’s encoding scheme.
The Global Research Collaboration of Network Meta-Analysis: A Social Network Analysis
2016
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Ranking Lists and European Framework Programmes
2011
The operational context for higher education institutions has become increasingly competitive: universities have to compete on national and international markets for students, staff, funding and prestige. The emergence of various markets, market mechanisms and competition in higher education have become a well-established and much discussed fact, and have shaped the dynamics of the higher education arena (Enders & Jongbloed 2007; Texeira et al. 2004) In a global competition of knowledge societies, higher education institutions have been vested with the task of economic and social change, and are expected to contribute to the competitiveness of nationstates as well as their local communities.
Tournament structure and nations' success in women's professional tennis
2007
The relationship between domestic professional tournament structure in women's tennis and the subsequent professional ranking success of a nation's female players is examined. The 2003 women's professional tennis tournament calendar provided the distribution of events in 33 countries. Criteria used to classify nations' success in women's professional tennis were as follows: number of players with Women's Tennis Association (WTA) points, number of players with Top 200 rankings, and the combined WTA ranking of a nation's Top 5 female players. Pearson product - moment correlations were performed between the number of tournaments and the three criteria. Considerable variation was observed in th…
How does serendipity affect diversity in recommender systems? A serendipity-oriented greedy algorithm
2018
Most recommender systems suggest items that are popular among all users and similar to items a user usually consumes. As a result, the user receives recommendations that she/he is already familiar with or would find anyway, leading to low satisfaction. To overcome this problem, a recommender system should suggest novel, relevant and unexpected i.e., serendipitous items. In this paper, we propose a serendipity-oriented, reranking algorithm called a serendipity-oriented greedy (SOG) algorithm, which improves serendipity of recommendations through feature diversification and helps overcome the overspecialization problem. To evaluate our algorithm, we employed the only publicly available datase…
Ranking-Oriented Collaborative Filtering: A Listwise Approach
2016
Collaborative filtering (CF) is one of the most effective techniques in recommender systems, which can be either rating oriented or ranking oriented. Ranking-oriented CF algorithms demonstrated significant performance gains in terms of ranking accuracy, being able to estimate a precise preference ranking of items for each user rather than the absolute ratings (as rating-oriented CF algorithms do). Conventional memory-based ranking-oriented CF can be referred to as pairwise algorithms. They represent each user as a set of preferences on each pair of items for similarity calculations and predictions. In this study, we propose ListCF, a novel listwise CF paradigm that seeks improvement in bot…
Learning Improved Feature Rankings through Decremental Input Pruning for Support Vector Based Drug Activity Prediction
2010
The use of certain machine learning and pattern recognition tools for automated pharmacological drug design has been recently introduced. Different families of learning algorithms and Support Vector Machines in particular have been applied to the task of associating observed chemical properties and pharmacological activities to certain kinds of representations of the candidate compounds. The purpose of this work, is to select an appropriate feature ordering from a large set of molecular descriptors usually used in the domain of Drug Activity Characterization. To this end, a new input pruning method is introduced and assessed with respect to commonly used feature ranking algorithms.
Projection Clustering Unfolding: A New Algorithm for Clustering Individuals or Items in a Preference Matrix
2020
In the framework of preference rankings, the interest can lie in clustering individuals or items in order to reduce the complexity of the preference space for an easier interpretation of collected data. The last years have seen a remarkable flowering of works about the use of decision tree for clustering preference vectors. As a matter of fact, decision trees are useful and intuitive, but they are very unstable: small perturbations bring big changes. This is the reason why it could be necessary to use more stable procedures in order to clustering ranking data. In this work, a Projection Clustering Unfolding (PCU) algorithm for preference data will be proposed in order to extract useful info…
Car style-holon recognition in computer-aided design
2019
Abstract Multi-scale design can presumably stimulate greater intelligence in computer-aided design (CAD). Using the style-holon concept, this paper proposes a computational approach to address multi-scale style recognition for automobiles. A style-holon is both a whole—it contains sub-styles of which it is composed—as well as a part of a broader style. In this paper, we first apply a variable precision rough set-based approach to car evaluation and ranking. Secondly, we extracted and subsequently computed the each car's characteristic lines from the CAD models. Finally, we identified style-holons using the property of a double-headed style-holon. A style-holon is necessarily included in a t…
European Energy Efficiency Evaluation Based on the Use of Super-Efficiency Under Undesirable Outputs in SBM Models
2020
Although Data Envelopment Analysis models have been intensively used for measuring efficiency, the inclusion of undesirable outputs has extended their use to analyse relevant fields such as environmental efficiency. In this context, slacks-based measure (SBM) models offer a remarkable alternative, largely due to their ability to deal with undesirable outputs. Additionally, super-efficiency evaluation in DEA is a useful complementary analysis for ranking the performance of efficient DMUs and even mandatory for dynamic efficiency evaluation. An extension to this approach in the presence of undesirable outputs is here introduced and then applied in the context of the environmental efficiency i…