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We study the geometry and topology of the large-scale structure traced by galaxy clusters in numerical simulations of a box of side 320 $h^{-1}$ Mpc, and compare them with available data on real clusters. The simulations we use are…

Astrophysics · Physics 2020-11-25 P. Coles , R. C. Pearson , S. Borgani , M. Plionis , L. Moscardini

Traditional clustering identifies groups of objects that share certain qualities. Tangles do the converse: they identify groups of qualities that often occur together. They can thereby discover, relate, and structure types: of behaviour,…

Artificial Intelligence · Computer Science 2024-05-15 Reinhard Diestel

Mixed data comprises both numeric and categorical features, and mixed datasets occur frequently in many domains, such as health, finance, and marketing. Clustering is often applied to mixed datasets to find structures and to group similar…

Machine Learning · Computer Science 2019-03-20 Amir Ahmad , Shehroz S. Khan

Generalisability and transportability of clinical prediction models (CPMs) refer to their ability to maintain predictive performance when applied to new populations. While CPMs may show good generalisability or transportability to a…

Methodology · Statistics 2024-12-06 Kritchavat Ploddi , Matthew Sperrin , Glen P. Martin , Maurice M. O'Connell

One important reason for the use of field categorization in bibliometrics is the necessity to make citation impact of papers published in different scientific fields comparable with each other. Raw citations are normalized by using…

Digital Libraries · Computer Science 2018-04-18 Robin Haunschild , Hermann Schier , Werner Marx , Lutz Bornmann

Citation analysis of the scientific literature has been used to study and define disciplinary boundaries, to trace the dissemination of knowledge, and to estimate impact. Co-citation, the frequency with which pairs of publications are…

We propose a representation of science as a citation-density landscape and investigate scaling rules with the field-specific citation density as a main topological property. We focus on the size-dependence of several main bibliometric…

Physics and Society · Physics 2007-07-24 Anthony F. J. van Raan

Topic models are a popular tool for clustering and analyzing textual data. They allow texts to be classified on the basis of their affiliation to the previously calculated topics. Despite their widespread use in research and application, an…

Artificial Intelligence · Computer Science 2024-03-07 Johannes Hirth , Tom Hanika

Scientific fields are often mapped using citations and metadata, despite knowledge being transmitted primarily through content. We introduce an 'inside-out' approach that reconstructs field structure directly from text by representing each…

Social and Information Networks · Computer Science 2026-01-22 Seorin Kim , Vincent Holst , Vincent Ginis

In the mining industry, many reports are generated in the project management process. These past documents are a great resource of knowledge for future success. However, it would be a tedious and challenging task to retrieve the necessary…

Information Retrieval · Computer Science 2021-11-08 Yasuko Okamoto , Thirunavukarasu Balasubramaniam , Richi Nayak

We study supervised learning problems using clustering constraints to impose structure on either features or samples, seeking to help both prediction and interpretation. The problem of clustering features arises naturally in text…

Machine Learning · Computer Science 2016-09-20 Vincent Roulet , Fajwel Fogel , Alexandre d'Aspremont , Francis Bach

The basic classification techniques for organizing information are thesauri, taxonomy and faceted classification. Topic map is relatively a new entrant to this information space. Topic map standard describes how complex relationships…

Digital Libraries · Computer Science 2010-03-19 Rajkumar Kannan

Graphs are commonly used to represent and visualize causal relations. For a small number of variables, this approach provides a succinct and clear view of the scenario at hand. As the number of variables under study increases, the graphical…

Machine Learning · Statistics 2023-08-16 Santtu Tikka , Jouni Helske , Juha Karvanen

The rapid growth of scientific literature has made it difficult for the researchers to quickly learn about the developments in their respective fields. Scientific document summarization addresses this challenge by providing summaries of the…

Computation and Language · Computer Science 2017-06-13 Arman Cohan , Nazli Goharian

This paper aims to use term clustering to build a modular ontology according to core ontology from domain-specific text. The acquisition of semantic knowledge focuses on noun phrase appearing with the same syntactic roles in relation to a…

Information Retrieval · Computer Science 2019-01-29 Ziwei Xu , Mounira Harzallah , Fabrice Guillet

Group-based Trajectory Modeling (GBTM) is applied to the citation curves of articles in six journals and to all citable items in a single field of science (Virology, 24 journals), in order to distinguish among the developmental trajectories…

Digital Libraries · Computer Science 2013-05-01 Susanne Baumgartner , Loet Leydesdorff

The uptake of machine learning (ML) approaches in the social and health sciences has been rather slow, and research using ML for social and health research questions remains fragmented. This may be due to the separate development of…

Now a day's, search engines are been most widely used for extracting information's from various resources throughout the world. Where, majority of searches lies in the field of biomedical for retrieving related documents from various…

Information Retrieval · Computer Science 2009-12-14 Jayanthi Manicassamy , P. Dhavachelvan

Citations in scholarly work serve the essential purpose of acknowledging and crediting the original sources of knowledge that have been incorporated or referenced. Depending on their surrounding textual context, these citations are used for…

Digital Libraries · Computer Science 2023-09-19 Yang Zhang , Yufei Wang , Kai Wang , Quan Z. Sheng , Lina Yao , Adnan Mahmood , Wei Emma Zhang , Rongying Zhao

The data mining technique of time series clustering is well established in many fields. However, as an unsupervised learning method, it requires making choices that are nontrivially influenced by the nature of the data involved. The aim of…

Econometrics · Economics 2018-07-19 Iwo Augustyński , Paweł Laskoś-Grabowski
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