Results 71 to 80 of about 8,324 (219)
Improving a tf-idf weighted document vector embedding
CoRR, 2019 We examine a number of methods to compute a dense vector embedding for a document in a corpus, given a set of word vectors such as those from word2vec or GloVe. We describe two methods that can improve upon a simple weighted sum, that are optimal in the sense that they maximizes a particular weighted cosine similarity measure.
openaire +2 more sources
ANALISIS PROGRAM MAKAN BERGIZI GRATIS DENGAN SUPPORT VECTOR MACHINE (SVM) PADA APLIKASI X
JSiI (Jurnal Sistem Informasi)The Free Nutritious Meal Program (MBG), which represents a priority program of President Prabowo Subianto, has garnered widespread attention from Indonesian society. This program has received sympathy from various groups, including students and informal
Sekar Cinta Amaria, Nurtriana Hidayati
doaj +1 more source
Revenue Recognition Comparability and Analysts’ Disclosure Processing Costs
Journal of Accounting Research, EarlyView.ABSTRACT I examine whether the FASB's revenue recognition guidance under ASC 606 influences revenue comparability across firms and industries and whether revenue comparability reduces analysts’ disclosure processing costs. I extract firms’ revenue policy disclosures from 10‐K filings to measure their textual similarity and compare revenue policies ...
ANDREA TILLET
wiley +1 more source
Demand Estimation with Text and Image Data
The RAND Journal of Economics, EarlyView.ABSTRACT We propose a demand estimation approach that leverages unstructured data to infer substitution patterns. Using pre‐trained deep learning models, we extract embeddings from product images and textual descriptions and incorporate them into a mixed logit demand model.
Giovanni Compiani +2 more
wiley +1 more source
Asia-Pacific Journal of Financial Studies, EarlyView.Abstract This study develops an explainable machine learning model to predict cryptocurrency delistings using Binance data. It combines quantitative indicators (price, volume) with qualitative data from real‐time news and Reddit. Latent Dirichlet Allocation (LDA) is used to extract topic trends and community reactions, which are transformed into time ...
Sungju Yang, Hunyeong Kwon
wiley +1 more source
Creativity and Innovation Management, Volume 34, Issue 4, Page 991-1012, December 2025.ABSTRACT Traditional techniques for evaluating creative outcomes are typically based on evaluations made by human experts. These methods suffer from challenges such as subjectivity, biases, limited availability, ‘crowding’, and high transaction costs. We propose that large language models (LLMs) can be used to overcome these shortcomings.
Theresa Kranzle, Katelyn Sharratt
wiley +1 more source
A gene pathway enrichment method based on improved TF-IDF algorithm. [PDF]
Biochem Biophys Rep, 2023 Xu S, Leng Y, Feng G, Zhang C, Chen M.
europepmc +1 more source
A qualitative assessment of quantitative easing sentiment
Economic Inquiry, EarlyView.Abstract This mixed‐method study undertakes a comprehensive inquiry of the public discourse on social media surrounding quantitative easing (QE) across the US, the UK, and the European Union. Utilizing a unique tweet dataset, we reveal the sentiment polarity toward QE policy to be strongly negative, at 71.27%, with positive sentiment a mere 4.25 ...
Niamh Wylie, Martha O’Hagan‐Luff
wiley +1 more source
Enhancing Fake News Detection with Word Embedding: A Machine Learning and Deep Learning Approach
ComputersThe widespread dissemination of fake news on social media has necessitated the development of more sophisticated detection methods to maintain information integrity.
Mutaz A. B. Al-Tarawneh +4 more
doaj +1 more source
Success and failure in England's patent system: New evidence from patent applications, 1783–1834
The Economic History Review, EarlyView.Abstract Our understanding of the relationship between the English patent system and technical change during the industrial revolution is based entirely on the study of successful patents. We address this feature by providing the first study of unsuccessful patent applications in England during the first industrial revolution.
Stephen D. Billington, Joe Lane
wiley +1 more source