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169,051 papers · 148 categories

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18355370 · Jun 202019922001200920182026
48 results for scholarly articles

Study analyzes Facebook reactions to scholarly articles.

problem Lack of analysis on click-based responses to scholarly content.
method Developed a new dataset of Facebook Reactions, analyzed statistical trends, and trained/tested supervised learning algorithms.
result Preliminary tests suggest stratification in user following based on page subject matter.

Deep learning captures semantic structure of large documents.

problem Understanding complex, structured documents like scholarly articles and business reports.
method Deep learning-based document ontology to capture semantic structure and domain-specific concepts.
result The ontology enhances semantic indexing for better understanding by humans and machines.

This paper automates mining of COVID-19 scholarly articles using machine learning.

problem Time-consuming and impractical manual extraction of relevant COVID-19 research articles.
method Used machine learning approaches, specifically clustering and parallel one-class support vector machines (OCSVMs), on the CORD-19 dataset.
result Parallel OCSVMs outperform other methods for both original and reduced feature space.

Paper proposes a method to discover topic evolutions from text data.

problem Difficulty in identifying new research topics from large text data.
method Uses sparseness-constrained Non-negative Matrix Factorization with generalized Jensen-Shannon divergence.
result Extracts more prominent topics and visualizes term-topic relationships.

Framework uses deep learning to analyze large documents and identify their logical structure.

problem Analyzing large, multi-themed documents with diverse topics.
method Deep learning techniques to model and extract logical and semantic structure.
result Framework effectively identifies and classifies different sections of documents.

Machine learning identifies types of alterations in historical manuscripts.

problem Understanding and categorizing alterations in historical manuscripts.
method Alteration Latent Dirichlet Allocation (alterLDA) model.
result High performance in recognizing alterations on labelled data, and interesting insights on unlabelled data.

Study adds memory effect to Solow-Swan model for more accurate economic growth modeling.

problem Inaccuracies in classical Solow-Swan model in capturing long-term dynamics.
method Introduced fractional calculus with Caputo derivative into Solow-Swan framework.
result Fractional-order model shows significant impact on capital accumulation and stability.

The study uses supervised learning to classify research data by discipline.

problem Automatically categorizing research data by discipline for scientometric analysis.
method Used a large dataset of 609,524 records for training and evaluation, employing tree-based models and neural networks.
result Multi-layer perceptron models outperformed Long Short-Term Memory models in multi-label classification tasks.

Quantum mechanics models human perception and decision-making, offering a new approach to understanding social dynamics.

problem Understanding the complex interactions between individuals and groups in social networks.
method Developed a simple computational code based on quantum mechanics principles to model human perception and decision-making.
result Quantum-inspired models can help explain differences in individual and group behavior.

Survey of methods to incorporate external knowledge into stock price prediction.

problem Challenges in predicting stock prices due to market volatility and non-linearity.
method Survey of methods for acquiring and incorporating external knowledge into stock price prediction models.
result Systematic synthesis of previous studies on external knowledge types and their application in stock price prediction.

Defines Learning Analytics' foundational structure and scope.

problem Lack of theoretical foundation in Learning Analytics.
method Proposes an axiomatic theory based on psychological learning and LA methodology.
result Clarifies the epistemological stance of Learning Analytics and its limitations.

New method improves traffic forecasting models by adapting to spatial shifts.

problem Improving traffic forecasting models' ability to handle spatial shifts over years.
method Proposes a novel Mixture of Experts (MoE) framework for spatiotemporal models.
result Significant improvement in performance for handling spatial distribution shifts.

This paper examines if CTE risk measure aligns with profit-maximizing risk capital allocations.

problem Whether CTE risk measure aligns with profit-maximizing risk capital allocations.
method Exhaustive probabilistic model settings analysis.
result CTE risk measure may align with profit-maximizing risk capital allocations under certain conditions.

Automatic classification of scientific articles based on common characteristics is an interesting problem with many applications in digital library and information retrieval systems. Properly organized articles can be useful for automatic generation of taxonomies in scientific writings, textual summarization, efficient…

2012-12-21abs ↗pdf ↗

Measuring the impact of scientific articles is important for evaluating the research output of individual scientists, academic institutions and journals. While citations are raw data for constructing impact measures, there exist biases and potential issues if factors affecting citation patterns are not properly account…

2015-02-25abs ↗pdf ↗

Graph Neural Networks improve demand forecasting by considering article relationships.

problem Forecasting independent article-level predictions without considering related articles.
method Integrating GNN encoder into DeepAR model and using article attribute similarity to build graphs.
result The proposed approach consistently outperforms non-graph benchmarks and produces useful article embeddings.

Models predict community interest in news articles with high accuracy.

problem Predict community-specific interest in news articles using content features.
method Computed content-based features on 60K articles from 4 communities. Trained and tested models over 3 time periods.
result Models can classify articles into communities with high accuracy (ROC AUC 0.81 to 1.0).

This article is a prologue to the article "Why Markets are Inefficient: A Gambling 'Theory' of Financial Markets for Practitioners and Theorists." It presents important background for that article --- why gambling is important, even necessary, for real-world traders --- the reason for the superiority of the strategic/g…

2018-01-07abs ↗pdf ↗

This paper connects foliations of the plane to non-Hausdorff 1-manifolds.

problem Connecting foliations of the plane to non-Hausdorff 1-manifolds.
method Establishes a connection between foliations of the plane and non-Hausdorff 1-dimensional manifolds.
result Establishes a beautiful connection between foliations of the plane and non-Hausdorff 1-dimensional manifolds.

Using H. Donnelly result from the article "Eta Invariants for G-Spaces" we calculate the eta invariants of the signature operator for almost all 7-dimensional flat manifolds with cyclic holonomy group. In all cases this eta invariants are an integer numbers. The article was motivated by D. D. Long and A. Reid article "…

2010-01-08abs ↗pdf ↗

This encyclopedia article briefly reviews without proofs some of the main results in cotangent bundle reduction. The article recalls most the necessary prerequisites to understand the main results.

2005-08-31abs ↗pdf ↗

This article is one of three highly influential articles on the topology of manifolds written by Robert D. Edwards in the 1970's but never published. It presents the initial solutions of the fabled Double Suspension Conjecture. (The other two articles are: 'Approximating certain cell-like maps by homeomorphisms' and 'T…

2006-10-18abs ↗pdf ↗

Paper proposes a new trading strategy using corporate event detection from news articles.

problem Predicting stock movements based on corporate events from news articles.
method Bi-level event detection model: low-level for token-level event identification, high-level for article-level event identification.
result The proposed strategy outperforms existing models in stock prediction metrics.

This encyclopedia article briefly reviews without proofs some of the main results in symplectic reduction. The article recalls most the necessary prerequisites to understand the main results, namely, group actions, momentum maps, and coadjoint orbits, among others.

2005-08-31abs ↗pdf ↗

The profusion of online news articles makes it difficult to find interesting articles, a problem that can be assuaged by using a recommender system to bring the most relevant news stories to readers. However, news recommendation is challenging because the most relevant articles are often new content seen by few users. …

2013-03-04abs ↗pdf ↗

This is the first of two articles in which we give a proof - for a broad class of four-manifolds - of Witten's conjecture that the Donaldson and Seiberg-Witten series coincide, at least through terms of degree less than or equal to c-2, where c is a linear combination of the Euler characteristic and signature of the fo…

2000-07-31abs ↗pdf ↗