In this work, we propose two novel (groups of) methods for unsupervised feature ranking and selection. The first group includes scores (Genie3 score, RandomForest score) that are computed from ensembles of predictive clustering trees. second method is URelief, the extension Relief family algorithms. Using 26 benchmark data sets 5 baselines, show both Genie3 score (computed ensemble extra trees)...

due to increasing importance of desertification challenges and its consequences the necessity of sustainabledevelopment achievement in arid and semi-arid regions is essential in order to avoid limited sources asting, increase the efficiency of controlling, reclamation and restoration projects of natural areas. based on the iterature review, it has been recognized that combating desertification ...

We introduce a simple, non-linear mention-ranking model for coreference resolution that attempts to learn distinct feature representations for anaphoricity detection and antecedent ranking, which we encourage by pre-training on a pair of corresponding subtasks. Although we use only simple, unconjoined features, the model is able to learn useful representations, and we report the best overall sc...

We present work on building a global long-tailed ranking of entities across multiple languages using Wikipedia and Freebase knowledge bases. We identify multiple features and build a model to rank entities using a ground-truth dataset of more than 10 thousand labels. The final system ranks 27 million entities with 75% precision and 48% F1 score. We provide performance evaluation and empirical e...

This paper describes our participation in the Triple Scoring task of WSDM Cup 2017, which aims at ranking triples from a knowledge base for two type-like relations: profession and nationality. We introduce a supervised ranking method along with the features we designed for this task. Our system has been top ranked with respect to average score difference and 2nd best in terms of Kendall’s tau.

Data envelopment analysis (DEA) with considering the best condition for each decision making unit (DMU) assesses the relative efficiency for it and divides a homogenous group of DMUs in to two categories: efficient and inefficient, but traditional DEA models can not rank efficient DMUs. Although some models were introduced for ranking efficient DMUs, Franklin Lio & Hsuan peng (2008), proposed a...

The India Rankings 2020 was announced the 5th annual edition of ranking for higher educational institutions in based on National Institutional Ranking Framework (NIRF). impact NIRF among is progressive their output, outcomes, and outreach to society. government also concentrating several policy decisions education sector results Rankings. This paper focused study Research Performance (RP) param...

National Institutional Ranking Framework (NIRF) was launched on 29 September 2015 by the Ministry of Human Resource Development, Government India to rank academic & research institutions across country. The NIRF E-release 2020 held 11th June 2020. present study analyses top 100 Universities in terms visualisation data, relationship ranking with parameters, and relations among these paramete...

Manifold Ranking is a graph-based ranking algorithm being successfully applied to retrieve images from multimedia databases. Given a query image, Manifold Ranking computes the ranking scores of images in the database by exploiting the relationships among them expressed in the form of a graph. Since Manifold Ranking effectively utilizes the global structure of the graph, it is significantly bett...