Event Detection and Classification in Hungarian Natural Texts

Subecz, Zoltán

doi:10.19044/esj.2019.v15n21p411

Cited by 5 publications

(4 citation statements)

References 6 publications

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“…Subecz Z first extracted n graphs as the features of the system call sequence and then used support vector machines to classify the trajectories according to the similarity of the trajectories of known problems [12]. Ma et al introduced the specific implementation of the text classification system in detail, which provided a basis for the subsequent text classification research [13].…”

Section: Introductionmentioning

confidence: 99%

Analysis and Simulation of Multimedia English Auxiliary Handle Based on Decision Tree Algorithm

Yan

2020

Complexity

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In this paper, through the improved decision tree algorithm, the handles in multimedia English assistance are parsed and simulated. In order to better perceive the sense of language in English composition and improve the rationality of intelligent evaluation, an N element based on association analysis is proposed. Sense value quantification calculates its support in the corpus by obtaining N-tuples of the composition. If the degree of support is lower than the threshold, the part where the language sense problem occurs is analyzed, and the type of language sense problem is judged for the students to provide assistance in modifying the composition. In addition, this paper also extracts word features, sentence features, and text structure features in the composition to fit the English handles analytical score. By testing the test set, the experiment shows that, by extracting the language sense features of the candidate’s English composition, it can not only judge whether there is a problem with the language sense of the candidate, but also provide a basis for the overall evaluation of the composition.

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Section: Introductionmentioning

confidence: 99%

Analysis and Simulation of Multimedia English Auxiliary Handle Based on Decision Tree Algorithm

Yan

2020

Complexity

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“…Since the importance of events as quasi-identifiers has been emphasized in this study, the events have to be extracted from the texts alongside the arguments of these events. This process is known as Event Extraction [76,77,[91][92][93].…”

Section: Automatized Workflows For Pseudonymizationmentioning

confidence: 99%

Challenges and Open Problems of Legal Document Anonymization

Csányi

Nagy²,

Vági

et al. 2021

Symmetry

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Data sharing is a central aspect of judicial systems. The openly accessible documents can make the judiciary system more transparent. On the other hand, the published legal documents can contain much sensitive information about the involved persons or companies. For this reason, the anonymization of these documents is obligatory to prevent privacy breaches. General Data Protection Regulation (GDPR) and other modern privacy-protecting regulations have strict definitions of private data containing direct and indirect identifiers. In legal documents, there is a wide range of attributes regarding the involved parties. Moreover, legal documents can contain additional information about the relations between the involved parties and rare events. Hence, the personal data can be represented by a sparse matrix of these attributes. The application of Named Entity Recognition methods is essential for a fair anonymization process but is not enough. Machine learning-based methods should be used together with anonymization models, such as differential privacy, to reduce re-identification risk. On the other hand, the information content (utility) of the text should be preserved. This paper aims to summarize and highlight the open and symmetrical problems from the fields of structured and unstructured text anonymization. The possible methods for anonymizing legal documents discussed and illustrated by case studies from the Hungarian legal practice.

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“…As such, ANNs' methodology for analyzing texts, drawing conclusions, and forecasting economic processes continue to develop and provide more accurate predictions. (Subecz, 2019) The objective of this study is to assess the value of articles published in online trade magazines that cover the stock market and the economy in the context of specific commodity exchange products. Specifically, we investigate the relationship between news articles published in these trade magazines and the changes in crude oil prices, with the aim of predicting future prices.…”

Section: Introductionmentioning

confidence: 99%

Keyword Research-based stock market oil price forecast validity test with neural network

Barta,

Molnár

2023

Gradus

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Stock market and global economic processes are often based on speculation, and in certain oligopoly markets, decisions are preceded by the prediction of the expected decisions of other players, i.e. we can also speak of speculative operation. In today's fast-paced world, the online press has a great influence on opinion formation through expert articles and analyses. In this article, we examine the extent to which Wall Street Journal articles influence or can influence investor inclination. In other words, the future price change can be predicted from the analysis of the articles, or more precisely, how effectively it can be predicted.

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Event Detection and Classification in Hungarian Natural Texts

Cited by 5 publications

References 6 publications

Analysis and Simulation of Multimedia English Auxiliary Handle Based on Decision Tree Algorithm

Analysis and Simulation of Multimedia English Auxiliary Handle Based on Decision Tree Algorithm

Challenges and Open Problems of Legal Document Anonymization

Keyword Research-based stock market oil price forecast validity test with neural network

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