標(biāo)題: Titlebook: Data Mining; 17th Australasian Co Thuc D. Le,Kok-Leong Ong,Graham Williams Conference proceedings 2019 Springer Nature Singapore Pte Ltd. 2 [打印本頁] 作者: Fuctionary 時(shí)間: 2025-3-21 17:47
書目名稱Data Mining影響因子(影響力)
書目名稱Data Mining影響因子(影響力)學(xué)科排名
書目名稱Data Mining網(wǎng)絡(luò)公開度
書目名稱Data Mining網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Data Mining被引頻次
書目名稱Data Mining被引頻次學(xué)科排名
書目名稱Data Mining年度引用
書目名稱Data Mining年度引用學(xué)科排名
書目名稱Data Mining讀者反饋
書目名稱Data Mining讀者反饋學(xué)科排名
作者: 執(zhí)拗 時(shí)間: 2025-3-21 23:17 作者: Indent 時(shí)間: 2025-3-22 03:31
Topic Representation using Semantic-Based Patternsodeling approaches apply probabilistic techniques to generate the list of topics from collections. Nevertheless, human understands, summarizes and discovers the topics based on the meaning of the content. Hence, the quality of the topic models can be improved by grasping the meaning from the content作者: irreducible 時(shí)間: 2025-3-22 08:20
Outlier Detection Based Accurate Geocoding of Historical Addressesuch databases can be analyzed individually to investigate, for example, changes in education, health, and emigration over time. Many of these historical databases contain addresses, and assigning geographical locations (latitude and longitude), the process known as ., will provide the foundation to 作者: 追逐 時(shí)間: 2025-3-22 11:54 作者: Intentional 時(shí)間: 2025-3-22 13:34
Estimating County Health Indices Using?Graph Neural Networksics at population level is analyzing data aggregated from individuals, typically through telephone surveys. Recent studies have found that social media can be utilized as an alternative population health surveillance system, providing quality and timely data at virtually no cost. In this paper, we f作者: Intentional 時(shí)間: 2025-3-22 17:33
Joint Sequential Data Prediction with Multi-stream Stacked LSTM Network navigation. Current developments in machine learning and computer systems bring the transportation industry numerous possibilities to improve their operations using data analyses on traffic flow sensor data. However, even state-of-art algorithms for time series forecasting perform well on some tran作者: 支柱 時(shí)間: 2025-3-23 00:46 作者: Debark 時(shí)間: 2025-3-23 01:32 作者: Conspiracy 時(shí)間: 2025-3-23 05:53
An Efficient Risk Data Learning with LSTM RNN risk data can be relied upon is to be ascertained till 2019. To facilitate the measurement and prediction of data quality, we propose an efficient approach to slide a piece of data from the big risk data and a model to train divergent Long Short-Term Memory (“LSTM”) Recurrent Neural Networks (“RNNs作者: 綠州 時(shí)間: 2025-3-23 12:29 作者: Genteel 時(shí)間: 2025-3-23 17:57
Classifying Imbalanced Road Accident Data Using Recurring Concept Drifties, but the results from the analysis can become outdated. We propose a stream classification framework with drift detection to signal and adapt when the factors associated with crash casualties change over time. We propose a drift detection framework, G-mean Adaptive drift Detection (GAD), which a作者: Obstruction 時(shí)間: 2025-3-23 21:08 作者: Robust 時(shí)間: 2025-3-23 23:07
Customer Wallet Share Estimation for Manufacturers Based on Transaction Dataase. One of the most important pieces of information is to estimate . for each individual customer. In the literature a related concept is often referred to as . that provides aggregated measures such as the business market share. The current trend in personalising marketing campaigns have led to mo作者: nocturnal 時(shí)間: 2025-3-24 02:28 作者: 中世紀(jì) 時(shí)間: 2025-3-24 09:34
Network Path Estimation in Uncertain Data via Entity Resolutionnal awareness. In this context, information obtained from multiple sources and at different points in time must be integrated. However, duplicate representations of the same entities in different data sources must be identified and merged to accurately infer and rank network paths. We extend previou作者: 斥責(zé) 時(shí)間: 2025-3-24 13:47 作者: 貧窮地活 時(shí)間: 2025-3-24 16:38 作者: 慢慢沖刷 時(shí)間: 2025-3-24 19:14
Data Mining978-981-15-1699-3Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: Indigence 時(shí)間: 2025-3-25 02:54 作者: MEN 時(shí)間: 2025-3-25 06:23
https://doi.org/10.1007/978-3-030-58157-2multi-valued (so that there are several correct output values for a given input) the problem becomes ill-posed, and many standard methods fail to find good solutions. However, optimisation problems based on multi-valued functions are relatively common. They include reverse robot kinematics, and the 作者: subordinate 時(shí)間: 2025-3-25 08:49
Akihiro Maehigashi,Sumaru Niidaodeling approaches apply probabilistic techniques to generate the list of topics from collections. Nevertheless, human understands, summarizes and discovers the topics based on the meaning of the content. Hence, the quality of the topic models can be improved by grasping the meaning from the content作者: 下級 時(shí)間: 2025-3-25 13:03
https://doi.org/10.1007/978-3-031-42141-9uch databases can be analyzed individually to investigate, for example, changes in education, health, and emigration over time. Many of these historical databases contain addresses, and assigning geographical locations (latitude and longitude), the process known as ., will provide the foundation to 作者: 預(yù)知 時(shí)間: 2025-3-25 18:03
https://doi.org/10.1007/978-3-031-42141-9te health-care programmes for the communities. This task acquires the prediction of population health status to be fast and accurate yet scalable to different population sizes. To satisfy these requirements, this paper proposes a method for automatic prediction of population health outcomes from soc作者: Friction 時(shí)間: 2025-3-25 21:54 作者: gustation 時(shí)間: 2025-3-26 03:05
Lecture Notes in Computer Science navigation. Current developments in machine learning and computer systems bring the transportation industry numerous possibilities to improve their operations using data analyses on traffic flow sensor data. However, even state-of-art algorithms for time series forecasting perform well on some tran作者: limber 時(shí)間: 2025-3-26 07:51
Detection of Football Spoilers on Twitter, forecasting or simply the comparison of multiple time series. Clustering is also an equally important and vast field in time series analysis. Different clustering algorithms provide different analysis aspects like the detection of classes or outliers. There are various approaches how to apply clus作者: 清晰 時(shí)間: 2025-3-26 11:03
https://doi.org/10.1007/978-3-319-98743-9umption does not hold are found in nearly every case where multi-class classification is applied. For example, in network traffic classification the actual number of classes often dramatically exceeds the number of classes known or labelled at training time. Various treatments have been proposed to 作者: fringe 時(shí)間: 2025-3-26 13:56 作者: engrave 時(shí)間: 2025-3-26 16:49 作者: monopoly 時(shí)間: 2025-3-27 00:09
Yuri Nishimura,Minoru Kobayashiies, but the results from the analysis can become outdated. We propose a stream classification framework with drift detection to signal and adapt when the factors associated with crash casualties change over time. We propose a drift detection framework, G-mean Adaptive drift Detection (GAD), which a作者: 整潔 時(shí)間: 2025-3-27 03:08
https://doi.org/10.1007/978-3-030-85071-5like European Union’s General Data Protection Regulation, which require firm capabilities to explain algorithmic decisions. Currently in the ML literature there does not seem to be a consensus on the definition of interpretability of a ML solution. Moreover, there is no agreement about the necessary作者: nitric-oxide 時(shí)間: 2025-3-27 07:44 作者: 機(jī)密 時(shí)間: 2025-3-27 10:27 作者: 留戀 時(shí)間: 2025-3-27 16:14
https://doi.org/10.1007/978-1-4419-7082-4nal awareness. In this context, information obtained from multiple sources and at different points in time must be integrated. However, duplicate representations of the same entities in different data sources must be identified and merged to accurately infer and rank network paths. We extend previou作者: FEMUR 時(shí)間: 2025-3-27 21:16 作者: 宴會 時(shí)間: 2025-3-28 01:23
https://doi.org/10.1007/978-981-15-1699-3artificial intelligence; association rules; computer crime; computer networks; computer systems; data ana作者: considerable 時(shí)間: 2025-3-28 02:37
978-981-15-1698-6Springer Nature Singapore Pte Ltd. 2019作者: GENRE 時(shí)間: 2025-3-28 09:56 作者: 吹牛者 時(shí)間: 2025-3-28 11:58 作者: reperfusion 時(shí)間: 2025-3-28 17:35
Improving Clustering via a Fine-Grained Parallel Genetic Algorithm with?Information Sharingcal optima. Secondly, PGAs offer improved execution time, as each subpopulation is processed in parallel on separate threads. Our technique advances an existing GA-based method called GenClust++, by employing a PGA along with a novel information sharing technique. We also compare our technique with 作者: 假設(shè) 時(shí)間: 2025-3-28 22:36
Topic Representation using Semantic-Based Patternss what existing topic modelling methods do. The semantically meaningful patterns were evaluated by applying the information filtering to semantic-based topic representation. The semantic based patterns were used as features for information filtering and were evaluated by comparing against popular in作者: esculent 時(shí)間: 2025-3-29 01:29 作者: Lamina 時(shí)間: 2025-3-29 06:50 作者: CERE 時(shí)間: 2025-3-29 09:21 作者: hazard 時(shí)間: 2025-3-29 12:54 作者: 使激動(dòng) 時(shí)間: 2025-3-29 18:28 作者: FEIGN 時(shí)間: 2025-3-29 21:35 作者: senile-dementia 時(shí)間: 2025-3-30 00:26
Interpretability of Machine Learning Solutions in Industrial Decision Engineeringrocess and is consistent with the best practices of project management in the ML settings. We illustrate the versatility and effortless applicability of CRISP-ML with examples across a variety of industries and types of ML projects.作者: 類似思想 時(shí)間: 2025-3-30 05:25
Customer Wallet Share Estimation for Manufacturers Based on Transaction Datald scenarios, there are circumstances where survey data are unavailable or unreliable. In this paper, we present a new customer wallet share estimation approach. In the proposed approach, a predictive model based on decision trees facilitates an accurate estimation of wallet shares for customers rel作者: 散開 時(shí)間: 2025-3-30 11:54 作者: 有權(quán) 時(shí)間: 2025-3-30 12:41
Interactive Deep Metric Learning for Healthcare Cohort Discoveryexperts to identify cohorts that are more relevant to a particular pre-defined purpose. Moreover, the proposed method leverages powerful deep learning-based embedding techniques to incrementally gain effective representations for the complex structures inherit in patient journey data. We experimenta作者: inspiration 時(shí)間: 2025-3-30 17:59
Gruppenprodukte (Group Products)cal optima. Secondly, PGAs offer improved execution time, as each subpopulation is processed in parallel on separate threads. Our technique advances an existing GA-based method called GenClust++, by employing a PGA along with a novel information sharing technique. We also compare our technique with 作者: Vsd168 時(shí)間: 2025-3-31 00:00 作者: hardheaded 時(shí)間: 2025-3-31 03:02 作者: 陰險(xiǎn) 時(shí)間: 2025-3-31 08:48
https://doi.org/10.1007/978-3-031-42141-9oughly evaluate our approach in the task of prediction of health indices of counties in the US via a large-scale dataset collected from Twitter. We also apply our proposed SPDF to two different textual features including latent topics and linguistic styles. We conduct two case studies: across-year v作者: 繁殖 時(shí)間: 2025-3-31 09:42
Eiji Watanabe,Takashi Ozeki,Takeshi Kohamath indices. We validate our proposed method by large-scale experiments on Twitter data for the task of predicting health indices of the US counties. Empirical results show a significant correlation with the reported health statistics, up?to a Spearman correlation coefficient (.) value of 0.69, and t作者: 碎石 時(shí)間: 2025-3-31 14:31
Lecture Notes in Computer Science specially developed to imitate real-world traffic flow dataset. In the end, we assess our multi-stream learning on a historical traffic flow dataset for Thessaloniki, Greece which is published by Hellenic Institute of Transport (HIT). We obtained better results on the short-term forecasts compared 作者: 描述 時(shí)間: 2025-3-31 21:01
Yuri Nishimura,Minoru Kobayashiences in phishing attack features detected for different countries. We have collected a real world Twitter dataset over 6 months and show that we are able to detect phishing successfully using US phishing models despite only a low level of phishing occurring in smaller populations such as New Zealan作者: 有惡臭 時(shí)間: 2025-3-31 21:45
