標(biāo)題: Titlebook: Data Mining; 20th Australasian Co Laurence A. F. Park,Heitor Murilo Gomes,Simeon Sim Conference proceedings 2022 The Editor(s) (if applicab [打印本頁] 作者: 寓言 時(shí)間: 2025-3-21 16:44
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: 設(shè)施 時(shí)間: 2025-3-21 21:46 作者: 有角 時(shí)間: 2025-3-22 00:36 作者: fructose 時(shí)間: 2025-3-22 04:40 作者: Texture 時(shí)間: 2025-3-22 11:39
Jim Duffy,Peter Koudal,Stephen Prattstructured query language before the rule-based formal query constructions. Three rules are exploited to generate a valid structured formal query. The web-based interactive application is developed to help maintainers access industrial maintenance knowledge graph which is constructed from text data.作者: Inexorable 時(shí)間: 2025-3-22 15:19
Hierarchical Topic Model Inference by?Community Discovery on?Word Co-occurrence NetworksCommunity Topic uncovers a topic hierarchy with a more coherent structure and a tighter relationship between parent and child topics. Community Topic is able to find this hierarchy more quickly and allows for on-demand sub- and super-topic discovery, facilitating corpus exploration by researchers.作者: Inexorable 時(shí)間: 2025-3-22 20:57 作者: 哥哥噴涌而出 時(shí)間: 2025-3-23 00:33 作者: 繁重 時(shí)間: 2025-3-23 04:53
Qingliang Zhang,Xinyue Shu,Quanwang Wu content preservation. To investigate this we compared the average similarity of multiple styles of text from the Corpus of Diverse Styles using a variety of sentence embedding methods and find that those embeddings which are created from aggregated word embeddings are style invariant, but those created by sentence embeddings are not.作者: 恃強(qiáng)凌弱 時(shí)間: 2025-3-23 08:08
T. A. Bhamra,J. Heeley,D. Tyleressing this complexity. Cluster definitions of Modal, Specialised and Aberrant are introduced as a descriptive framework on which to interpret said feature decomposition and to aid threshold setting. This strategy furthers the work introduced in [.] as refinement to an existing anomaly detection scheme.作者: dowagers-hump 時(shí)間: 2025-3-23 12:46
Co-model Structuring and Design Patternsworks or are derived from textbooks or engine benchmarks. . contains 2,500 samples of relational schema found in public code repositories which have been standardised to . syntax. We provide our gathering and transformation methodology, summary statistics, structural analysis, and discuss potential downstream research tasks in several domains.作者: 錯(cuò) 時(shí)間: 2025-3-23 17:55 作者: canvass 時(shí)間: 2025-3-23 20:13
Decomposition of Service Level Encoding for Anomaly Detectionessing this complexity. Cluster definitions of Modal, Specialised and Aberrant are introduced as a descriptive framework on which to interpret said feature decomposition and to aid threshold setting. This strategy furthers the work introduced in [.] as refinement to an existing anomaly detection scheme.作者: canonical 時(shí)間: 2025-3-23 22:48
: A Dataset for?Structures in?Relational Dataworks or are derived from textbooks or engine benchmarks. . contains 2,500 samples of relational schema found in public code repositories which have been standardised to . syntax. We provide our gathering and transformation methodology, summary statistics, structural analysis, and discuss potential downstream research tasks in several domains.作者: 排斥 時(shí)間: 2025-3-24 05:58
Improving Ads-Profitability Using Traffic-Fingerprints作者: Resistance 時(shí)間: 2025-3-24 09:09
Laurence A. F. Park,Heitor Murilo Gomes,Simeon Sim作者: BRAND 時(shí)間: 2025-3-24 13:00
A Temperature-Modified Dynamic Embedded Topic Modelal Debate Corpus, and the ACL Title and Abstract dataset show that the proposed model – nicknamed DETM-tau after the temperature parameter – has been able to improve the model’s perplexity and topic coherence for all datasets.作者: Folklore 時(shí)間: 2025-3-24 17:37 作者: 杠桿支點(diǎn) 時(shí)間: 2025-3-24 20:39
Graph Embeddings for?Non-IID Data Feature Representation Learningrepresentation is based on traffic speed, volume, and speed limit; the second representation is the graph embeddings learned from the traffic knowledge graph. Our experimental results show that the road network information captured in the knowledge graphs is crucial for predicting traffic risk level作者: ostrish 時(shí)間: 2025-3-25 00:02 作者: 浮雕 時(shí)間: 2025-3-25 06:28
WinDrift: Early Detection of?Concept Drift Using Corresponding and?Hierarchical Time Windowsomparing statistical distance between two windows of corresponding time period on each level. To evaluate the efficacy of WD, 4 real datasets and 10 reproducible synthetic datasets are used. A comparison with 5 existing state-of-the-art drift detection methods demonstrates that WinDrift detects drif作者: Peculate 時(shí)間: 2025-3-25 10:47 作者: enumaerate 時(shí)間: 2025-3-25 13:56
Interpretable Decisions Trees via?Human-in-the-Loop-Learningits. Moreover, we show that discrimination and characterisation rules are also well communicated using parallel coordinates. We confirm the merits of our approach by reporting results from a large usability study.作者: AMBI 時(shí)間: 2025-3-25 18:59
A Comparative Look at?the?Resilience of?Discriminative and?Generative Classifiers to?Missing Data ina was imbalanced. Specifically, F1 scores for LoGAN models were .80% for up to 20% of missing data rates in the temporal component of the dataset and .60% for missing rates from 40–100%. Non-deep generative models showed low performance with the introduction of missing data rates.作者: TOM 時(shí)間: 2025-3-25 21:13 作者: BUST 時(shí)間: 2025-3-26 02:31
Attractiveness Analysis for?Health Claims on?Food Packagesonsumer preference prediction. The experimental results show the proposed model achieves high prediction accuracy. Beyond the prediction model, as case studies, we proposed and validated three important attractiveness factors: specialised terminology, sentiment, and metaphor. The results suggest tha作者: 合同 時(shí)間: 2025-3-26 04:24
Song Guo,Xiaofei Liao,Yanmin Zhual Debate Corpus, and the ACL Title and Abstract dataset show that the proposed model – nicknamed DETM-tau after the temperature parameter – has been able to improve the model’s perplexity and topic coherence for all datasets.作者: 不足的東西 時(shí)間: 2025-3-26 11:44
https://doi.org/10.1007/978-3-319-28910-6 based on their learning difficulty in relation to other instances within the dataset. The proposed difficulty measures measure both the fluctuations in labeling during the construction process of the ensemble and the amount of resources required for the correct label. This provides the degree of di作者: Lipoma 時(shí)間: 2025-3-26 14:19 作者: Mechanics 時(shí)間: 2025-3-26 17:49
https://doi.org/10.1007/978-3-319-28910-6 the input single-cell data to make UMAP and PCA processes more efficient. We demonstrate that this approach can be applied to high-dimensional omics data exploration to visually validate informative molecule markers and cell populations identified from the UMAP-reduced dimensionality space.作者: LUCY 時(shí)間: 2025-3-26 22:24 作者: 造反,叛亂 時(shí)間: 2025-3-27 03:29 作者: 游行 時(shí)間: 2025-3-27 09:02
Arkato Gendole Anto,Fer Coendersits. Moreover, we show that discrimination and characterisation rules are also well communicated using parallel coordinates. We confirm the merits of our approach by reporting results from a large usability study.作者: pulmonary-edema 時(shí)間: 2025-3-27 09:27
New Ways of Category Managementa was imbalanced. Specifically, F1 scores for LoGAN models were .80% for up to 20% of missing data rates in the temporal component of the dataset and .60% for missing rates from 40–100%. Non-deep generative models showed low performance with the introduction of missing data rates.作者: 編輯才信任 時(shí)間: 2025-3-27 14:06
Jim Duffy,Peter Koudal,Stephen Prattclinical resources by avoiding unnecessary manual assessments. The objective of this paper is to propose an automatic initial frailty assessment approach which can quickly identify potential patients that require further frailty assessment by using patient’s relevant clinical notes to answer Tillbur作者: 公理 時(shí)間: 2025-3-27 19:05
Generative Tools for Co-designingonsumer preference prediction. The experimental results show the proposed model achieves high prediction accuracy. Beyond the prediction model, as case studies, we proposed and validated three important attractiveness factors: specialised terminology, sentiment, and metaphor. The results suggest tha作者: 鎮(zhèn)壓 時(shí)間: 2025-3-27 23:07 作者: 關(guān)節(jié)炎 時(shí)間: 2025-3-28 02:59
Qingliang Zhang,Xinyue Shu,Quanwang Wu relies on taking the cosine similarity of the sentence embeddings of the original and transferred sentence to determine if the content of the sentence, its meaning, hasn’t changed. This assumes however that such sentence embeddings are style invariant, which can result in inaccurate measurements of作者: 輕快走過 時(shí)間: 2025-3-28 07:27
Song Guo,Xiaofei Liao,Yanmin Zhur, conventional topic models fail to capture how such topics change as the collections evolve. To amend this, various researchers have proposed dynamic versions which are able to extract sequences of topics from timestamped document collections. Moreover, a recently-proposed model, the dynamic embed作者: 課程 時(shí)間: 2025-3-28 12:56 作者: arbiter 時(shí)間: 2025-3-28 16:36 作者: jeopardize 時(shí)間: 2025-3-28 20:50 作者: neologism 時(shí)間: 2025-3-29 01:10
Arkato Gendole Anto,Fer Coendersr data-driven decision-making. With time, changes may emerge in the statistical characteristics of this data - this is also known as .. A concept drift can be detected using a concept drift detector. An ideal detector should detect drift accurately and efficiently. However, these properties may not 作者: 脊椎動(dòng)物 時(shí)間: 2025-3-29 06:22 作者: DALLY 時(shí)間: 2025-3-29 09:28 作者: cogitate 時(shí)間: 2025-3-29 13:17
Arkato Gendole Anto,Fer Coenders. Moreover, the expert driving the learning (human-in-the-loop-learning) can steer the learning objective, not only for accuracy, but perhaps for discrimination or characterisation rules, where isolating one class is the primary objective. Moreover, the interaction enables humans to explore and gain作者: Cerebrovascular 時(shí)間: 2025-3-29 19:13
New Ways of Category Managementcation performances. Given the breakthrough of deep generative models in data generation, this paper proposes a conditional Generative Adversarial Network (GAN) based longitudinal classifier (LoGAN) to address this problem in longitudinal datasets. LoGAN is evaluated against commonly used and state-作者: Pantry 時(shí)間: 2025-3-29 19:49 作者: 百靈鳥 時(shí)間: 2025-3-30 01:40 作者: gimmick 時(shí)間: 2025-3-30 07:57
Jim Duffy,Peter Koudal,Stephen Pratts, such as drop-down lists and check-boxes, to construct queries. However, this requires multiple clicks and selections. Natural language queries, on the other hand, are more convenient and less restrictive for knowledge graphs navigation. In this paper, we propose a system that enables natural lang作者: 兩種語言 時(shí)間: 2025-3-30 09:23 作者: HAUNT 時(shí)間: 2025-3-30 14:11
Generative Tools for Co-designings of food products. They are popularly used by food manufacturers to attract consumers and promote their products. How to design and develop NLP tools to better support the food industry to predict the attractiveness of health claims has not yet been investigated. To bridge this gap, we propose a no作者: 杠桿支點(diǎn) 時(shí)間: 2025-3-30 17:20 作者: 貪心 時(shí)間: 2025-3-30 21:41 作者: AMITY 時(shí)間: 2025-3-31 03:31
https://doi.org/10.1007/978-981-19-8746-5artificial intelligence; classification; computational linguistics; computer networks; computer security作者: municipality 時(shí)間: 2025-3-31 05:35
978-981-19-8745-8The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor作者: anus928 時(shí)間: 2025-3-31 12:58
Conference proceedings 2022ng December 12–15, 2022.?.The 17 full papers included in this book were carefully reviewed and selected from 44 submissions. They were organized in topical sections as ?research track and application track. .作者: Fibrillation 時(shí)間: 2025-3-31 16:30 作者: reflection 時(shí)間: 2025-3-31 18:17
