作者: aristocracy 時間: 2025-3-21 20:34 作者: BROOK 時間: 2025-3-22 03:44 作者: Nomadic 時間: 2025-3-22 08:39
A Comparison of Neural Network Methods for Accurate Sentiment Analysis of Stock Market Tweetsnce of this task for financial institutions, models being used still lack high accuracy. Also, most of these models are not built specifically on stock market data. Therefore, there is still a need for a highly accurate model of sentiment classification that is specifically tuned and trained for sto作者: 低能兒 時間: 2025-3-22 12:10 作者: 突變 時間: 2025-3-22 13:21 作者: 突變 時間: 2025-3-22 18:00 作者: insecticide 時間: 2025-3-22 21:38
A Web Crawling Environment to Support Financial Strategies and Trend Correlation and extract relevant information. We collected all these instruments in a collaborative environment called ., offering a GUI to operate remotely. Finally, we describe an ongoing activity on semantic crawling and data analysis to discover trends and correlations in finance.作者: PUT 時間: 2025-3-23 05:04 作者: 背叛者 時間: 2025-3-23 06:05 作者: THROB 時間: 2025-3-23 12:04 作者: Lipohypertrophy 時間: 2025-3-23 15:16
Exploring Students Eating Habits Through Individual Profiling and Clustering Analysise importance of a healthy and balanced diet. To this end, understanding the real eating habits of people becomes fundamental for a better and more effective intervention to improve the students’ diet. In this paper we present two exploratory analyses based on centroid-based clustering that have the 作者: angiography 時間: 2025-3-23 21:48
Naresh Kumar Thakur,Sanjeev Rajputntities of interests, accounting for interdependencies among them. In finance, several of this quantities of interests (stock valuations, return, volatility) have been shown to be mutually influencing each other, making the prediction of such quantities a difficult task, especially while dealing wit作者: 生意行為 時間: 2025-3-23 23:36 作者: BAN 時間: 2025-3-24 04:09
Human Complement Receptor 1 Polymorphismsnear relationship. Although deep learning performs quite well, it has significant disadvantages such as a lack of transparency and limitations to the interpretability of the prediction. This is prone to practical problems in terms of accountability. Thus, we construct a multifactor model by using in作者: 裝勇敢地做 時間: 2025-3-24 10:25
Lei Yang,Shumin Liang,Binjie Zhunce of this task for financial institutions, models being used still lack high accuracy. Also, most of these models are not built specifically on stock market data. Therefore, there is still a need for a highly accurate model of sentiment classification that is specifically tuned and trained for sto作者: intrude 時間: 2025-3-24 12:28 作者: 控訴 時間: 2025-3-24 16:36 作者: VEIL 時間: 2025-3-24 20:48
J. Hanasz,V. I. Aksenov,G. P. Komrakovake a Bayesian approach to inference and model comparison in self-exciting processes. We discuss strategies to compute marginal likelihood estimates for the univariate Hawkes process, and describe a Bayesian model comparison scheme. We demonstrate on currency, cryptocurrency and equity limit order b作者: 感激小女 時間: 2025-3-25 03:10 作者: 過濾 時間: 2025-3-25 06:02
Writing and Editing Data Files,ack by release of difficulty parameters in the Rasch model with privacy protection using differential privacy. We provide a first proof of differential privacy in Rasch models and derive the minimum noise level in objective perturbation to guarantee a given privacy budget. We test the workflow in si作者: Visual-Acuity 時間: 2025-3-25 11:15 作者: cornucopia 時間: 2025-3-25 14:23
George Martin,Charles Ogburn,Curtis Spraguea is also useful to develop analytical services and for marketing purposes, often based on individual purchasing patterns. However, retail data and extracted models may also provide very sensitive information to possible malicious third parties. Therefore, in this paper we propose a methodology for 作者: olfction 時間: 2025-3-25 19:17 作者: savage 時間: 2025-3-25 20:47
https://doi.org/10.1007/978-3-030-13463-1artificial intelligence; commerce; data mining; data privacy; data security; internet; privacy; privacy pre作者: fabricate 時間: 2025-3-26 00:34
978-3-030-13462-4Springer Nature Switzerland AG 2019作者: 江湖郎中 時間: 2025-3-26 04:49 作者: agitate 時間: 2025-3-26 10:17 作者: Relinquish 時間: 2025-3-26 13:00
Conference proceedings 2019n Databases, ECML PKDD 2018, in Dublin, Ireland, in September 2018, namely:..MIDAS 2018. – Third Workshop on Mining Data for Financial Applications .and.PAP 2018. – Second International Workshop on Personal Analytics and Privacy...The 12 papers presented in this volume were carefully reviewed and selected from a total of 17 submissions...?.作者: PHAG 時間: 2025-3-26 17:38 作者: 文藝 時間: 2025-3-27 00:42
ECML PKDD 2018 Workshops978-3-030-13463-1Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: enlist 時間: 2025-3-27 01:42 作者: Nebulous 時間: 2025-3-27 09:09 作者: RUPT 時間: 2025-3-27 10:56
0302-9743 iscovery in Databases, ECML PKDD 2018, in Dublin, Ireland, in September 2018, namely:..MIDAS 2018. – Third Workshop on Mining Data for Financial Applications .and.PAP 2018. – Second International Workshop on Personal Analytics and Privacy...The 12 papers presented in this volume were carefully revie作者: 宏偉 時間: 2025-3-27 14:16 作者: 痛苦一生 時間: 2025-3-27 18:34 作者: CRUC 時間: 2025-3-28 00:46 作者: 圖畫文字 時間: 2025-3-28 05:54
Testing for Self-excitation in Financial Events: A Bayesian Approachor the univariate Hawkes process, and describe a Bayesian model comparison scheme. We demonstrate on currency, cryptocurrency and equity limit order book data that the test captures excitatory dynamics.作者: gout109 時間: 2025-3-28 09:46
0302-9743 cations .and.PAP 2018. – Second International Workshop on Personal Analytics and Privacy...The 12 papers presented in this volume were carefully reviewed and selected from a total of 17 submissions...?.978-3-030-13462-4978-3-030-13463-1Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: flammable 時間: 2025-3-28 11:42
Roberta J. M. Olson,Jay M. Pasachoffe suitability of depth-wise convolution and provide evidence for the advantages of neural network approach over existing methodologies. The proposed models produce mean reversion comparable to rolling-window linear regression’s results, allowing for greater flexibility while being less sensitive to market turbulence.作者: miscreant 時間: 2025-3-28 15:19
George Martin,Charles Ogburn,Curtis Spragueempirically assessing privacy risk in the releasing of individual purchasing data. The experiments on real-world retail data show that although individual patterns describe a summary of the customer activity, they may be successful used for the customer re-identifiation.作者: Pseudoephedrine 時間: 2025-3-28 21:40 作者: incision 時間: 2025-3-28 23:27 作者: Irrigate 時間: 2025-3-29 03:20
The Transition to Incipient Modern Algebra,t computationally expensive public key operations, while it is still secure and avoids precision losses. We report the runtime results on some real-world datasets, and discuss different security aspects and finally give an outlook on further improvements.作者: 小溪 時間: 2025-3-29 07:58 作者: stratum-corneum 時間: 2025-3-29 12:14 作者: 延期 時間: 2025-3-29 17:39 作者: 大喘氣 時間: 2025-3-29 19:55 作者: FLUSH 時間: 2025-3-29 23:56 作者: Mercurial 時間: 2025-3-30 04:52
Deep Factor Modelysis on the Japanese stock market and show that our deep factor model has better predictive capability than the traditional linear model or other machine learning methods. In addition, we illustrate which factor contributes to prediction.作者: intrude 時間: 2025-3-30 08:20
A Comparison of Neural Network Methods for Accurate Sentiment Analysis of Stock Market Tweetsque pre-processing technique, a shallow CNN achieves the best error rate, while a shallow LSTM, with a higher number of cells, achieves the highest accuracy of 92.7% compared to baseline of 79.9% using SVM. Building on this substantial improvement in the sentiment analysis of stock market tweets, we作者: PARA 時間: 2025-3-30 16:01
ICIE 1.0: A Novel Tool for Interactive Contextual Interaction Explanationsare flexible, and which ones are static). We introduce the . framework (Interactive Contextual Interaction Explanations) which enables users to view explanations of individual instances under different .. We will see that various contexts for the same case lead to different explanations, revealing d
