標題: Titlebook: Data Science; Third International Beiji Zou,Min Li,Zeguang Lu Conference proceedings 2017 Springer Nature Singapore Pte Ltd. 2017 Data ana [打印本頁] 作者: CRUST 時間: 2025-3-21 18:12
書目名稱Data Science影響因子(影響力)
書目名稱Data Science影響因子(影響力)學(xué)科排名
書目名稱Data Science網(wǎng)絡(luò)公開度
書目名稱Data Science網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Data Science被引頻次
書目名稱Data Science被引頻次學(xué)科排名
書目名稱Data Science年度引用
書目名稱Data Science年度引用學(xué)科排名
書目名稱Data Science讀者反饋
書目名稱Data Science讀者反饋學(xué)科排名
作者: phase-2-enzyme 時間: 2025-3-22 00:04
Research of Detection Algorithm for Time Series Abnormal Subsequence,rom time series data plays a very important role in data mining. In this paper, we focus on the abnormal subsequence detection. The original definition of . subsequences is defective for some kind of time series, in this paper we give a more robust definition which is based on the k nearest neighbor作者: 悠然 時間: 2025-3-22 03:22
An Improved SVM Based Wind Turbine Multi-fault Detection Method, was used to reduce the dimension of target features to 1-D, so that PCA output 1-D data can be used as label of support vector machine (SVM). Thus on the premise of not losing the prediction correctness, one model can detect the fault of 2 to 4 features, largely reduce the complexity of model build作者: 小步舞 時間: 2025-3-22 08:17
GPU Based Hash Segmentation Index for Fast T-overlap Query,fication framework, thus in low efficiency. Modern GPU has much higher parallelism as well as memory bandwidth than CPU and can be used to accelerate T-overlap query. In this paper, we use hash segmentation to divide inverted lists into segments, then design an efficient inverted index called GHSII 作者: Collected 時間: 2025-3-22 12:35 作者: Gum-Disease 時間: 2025-3-22 14:26 作者: Gum-Disease 時間: 2025-3-22 20:37
,Further Analysis of Candlestick Patterns’ Predictive Power,lp resolve the debate, this paper uses the data mining methods of pattern recognition, pattern clustering and pattern knowledge mining to research the predictive power of candlestick patterns. In addition, we propose the similarity match model and nearest neighbor-clustering algorithm to solve the p作者: ethnology 時間: 2025-3-22 23:53 作者: 開花期女 時間: 2025-3-23 04:04 作者: CARE 時間: 2025-3-23 06:34
Disease Prediction Based on Transfer Learning in Individual Healthcare,present disease prediction models based on transfer learning. Breast cancer disease data has been used to build our model. According to the neural networks, the basic model has been provided. With unlabeled data, transfer learning is a appropriate way to revise the module to increase accuracy. The t作者: AMPLE 時間: 2025-3-23 12:55 作者: Graves’-disease 時間: 2025-3-23 14:44
A New Approach to Dense Spectrum Analysis of Infrasonic Signals,rum which can leads to potential erroneous spectrum analysis. Hereby we propose a dense spectrum analysis algorithm combining all phase Fast Fourier Transform (apFFT) and Chirp Z-transform (CZT) to analyse dense low frequency signal. This is called all phase Chirp Z transform (apCZT). The apFFT spec作者: GEON 時間: 2025-3-23 18:19
Research on XDR Bill Compression Under Big Data Technology,arried on in this paper by using the big data technology based on the widely used XDR bill in communication industry. According to different application scenarios, this paper puts forward targeted compression strategy and technological implementation method and verify the high efficiency of associat作者: overbearing 時間: 2025-3-24 00:15 作者: 變形 時間: 2025-3-24 04:28 作者: conquer 時間: 2025-3-24 06:44 作者: 大約冬季 時間: 2025-3-24 13:56
A Cooperative Abnormal Behavior Detection Framework Based on Big Data Analytics,re. This paper proposes a cooperative framework to leverage the robustness of big data analytics and the power of ensemble learning techniques to detect the abnormal behavior. In addition to this proposal, we implement a large scale network abnormal traffic behavior detection system performed by the作者: Cacophonous 時間: 2025-3-24 17:17 作者: 追蹤 時間: 2025-3-24 20:17
Hierarchical Access Control Scheme of Private Data Based on Attribute Encryption,ta sharing is too single and soon on, we design a hierarchical access control scheme of private data based on attribute encryption. First, we construct a new algorithm based on attribute encryption, which divides encryption into two phases, and we can design two types of attributes encryption strate作者: Blood-Clot 時間: 2025-3-24 23:45
https://doi.org/10.1007/978-1-4615-3286-6uristic query order is proposed to solve the problem of load imbalance. Experiments are carried out on two real datasets and the results show that GSPS-TLLO outperforms the state-of-the-art GPU parallel T-overlap algorithms.作者: BURSA 時間: 2025-3-25 04:55
Master Data of Bill of Materialresults proved that desktop data greatly contributed to providing effective personalized reference words. Besides, the results demonstrated that a user’s long-term interest model performed steadier than work task context, but the most valuable words were the top-3 words extracted from the work context.作者: 跟隨 時間: 2025-3-25 11:33
Viola Katharina Klotz,Esther Wintherrvals are less than the ordinary frequency resolving power of Discrete Fourier Transform (DFT) and apFFT. The apCZT it is not only suitable for infrasonic signals but also in other dense spectrum analysis applications, such as voice, vibration, noise, electrocardiography, radar signals, power system harmonics and other engineering practice.作者: BATE 時間: 2025-3-25 12:57 作者: 移植 時間: 2025-3-25 18:35 作者: misshapen 時間: 2025-3-25 22:51 作者: 我要威脅 時間: 2025-3-26 00:55 作者: faultfinder 時間: 2025-3-26 06:15
A New Approach to Dense Spectrum Analysis of Infrasonic Signals,rvals are less than the ordinary frequency resolving power of Discrete Fourier Transform (DFT) and apFFT. The apCZT it is not only suitable for infrasonic signals but also in other dense spectrum analysis applications, such as voice, vibration, noise, electrocardiography, radar signals, power system harmonics and other engineering practice.作者: 性冷淡 時間: 2025-3-26 09:58
An Improved FP-Growth Algorithm Based on SOM Partition,th algorithm is executed in each subset, and association rules are mined. The experimental result shows that the improved algorithm reduces the memory consumption, and shortens the time of data mining. The processing capacity and efficiency of massive data is enhanced by the improved algorithm.作者: Mingle 時間: 2025-3-26 14:10
Hierarchical Access Control Scheme of Private Data Based on Attribute Encryption, the private data inferior to their permissions. And we outsource some complex operations of decryption to DSP to ensure high efficiency on the premise of privacy protection. Finally, we analyze the efficiency and the security of our scheme.作者: 讓空氣進入 時間: 2025-3-26 18:19 作者: 橫條 時間: 2025-3-26 22:32 作者: Kindle 時間: 2025-3-27 04:25 作者: biopsy 時間: 2025-3-27 06:17
Research of Detection Algorithm for Time Series Abnormal Subsequence,aracteristic of some special time series. To speed up the process of abnormal subsequence detection, we used the clustering method to optimize the outer loop ordering and early abandon subsequence which is impossible to be abnormal. The experiment results validate that the algorithm is correct and has a high efficiency.作者: 正式演說 時間: 2025-3-27 11:41
Research on Pattern Matching Method of Multivariate Hydrological Time Series,easure of similarity in sequences. Carrying out experiments on the hydrological data of Chu River, we conclude that the pattern matching method can effectively describe the overall characteristics of the multivariate time series, which has a good matching effect on the multivariate hydrological time series.作者: 兵團 時間: 2025-3-27 14:40
A Novel Recommendation Service Method Based on Cloud Model and User Personality, user characteristic attribute Web service recommendation is implemented by personalized collaborative filtering algorithm. The experimental results on the WS-Dream dataset show that our approach not only solves the drawbacks of the sparse user service, but also improves the recommend accuracy.作者: nephritis 時間: 2025-3-27 18:34 作者: CARK 時間: 2025-3-27 23:04
https://doi.org/10.1007/978-3-540-78973-4We judge the text whether it is positive or negative first, then choose the fine-grained emotional tendency. And we get good result with the test using COAE data set. Compared with other method for feature selection and other emotional library, we did better.作者: 連接 時間: 2025-3-28 02:20 作者: 長處 時間: 2025-3-28 07:52 作者: Decibel 時間: 2025-3-28 13:45
Conference proceedings 2017ngineers and Educators, ICPCSEE 2017 (originally ICYCSEE)?held in Changsha, China, in September 2017.?.The 112 revised full papers presented in these two volumes were carefully reviewed and selected from 987 submissions. The papers cover a wide range of topics related to Basic Theory and Techniques 作者: 征兵 時間: 2025-3-28 15:15
A Collaborative Filtering Recommendation Algorithm Based on the Difference and the Correlation of U to solve the problem that the algorithm is not accurate in spare dataset, we improve it by prefilling the vacancy of rating matrix. Experiment results show that this algorithm improves significantly the accuracy of the recommendation after prefilling the rating matrix.作者: 過分 時間: 2025-3-28 21:01
Partial Least Squares (PLS) Methods for Abnormal Detection of Breast Cells, we used the 10 features of breast cells to predict it, the results reaching upto 93.67% accuracy, it was very effective to predict and analyse whether the breast cells getting cancer, It had an important role in the diagnosis and prevention of breast cancer.作者: confide 時間: 2025-3-29 01:16
Research on Fuzzy Matching Query Algorithm Based on Spatial Multi-keyword,to this algorithm, which not only supports multiple POI queries, but also supports fault tolerance of the query keywords. The simulation results demonstrate that the proposed algorithm can improve the accuracy and efficiency of query.作者: Flatus 時間: 2025-3-29 03:34
Research on XDR Bill Compression Under Big Data Technology,ed method in practice. It solves the problem of occupying large storage and low analysis efficiency in areas like the storage of the massive XDR bill, pretreatment, aggregation. It provides valuable references for telecommunication-related researchers and engineering practitioner in respect of using the big data technology.作者: 有幫助 時間: 2025-3-29 07:57
Composite Graph Publication Considering Important Data,nce availability is whether the important data keep original value in a composite graph. We analysis the properties of important data of k triangle count, and provide a new method for synthesis graph publication. We show the application of this method in k triangle count, and the experimental results proved the accuracy of the method.作者: CHIP 時間: 2025-3-29 12:44 作者: 飛行員 時間: 2025-3-29 18:23 作者: FLAGR 時間: 2025-3-29 20:03
Disease Prediction Based on Transfer Learning in Individual Healthcare,works, the basic model has been provided. With unlabeled data, transfer learning is a appropriate way to revise the module to increase accuracy. The test results show that the algorithm is suitable for data classification, especially for unlabeled health data.作者: 北極人 時間: 2025-3-30 02:28 作者: Nibble 時間: 2025-3-30 07:01 作者: 暫時休息 時間: 2025-3-30 10:57 作者: 憂傷 時間: 2025-3-30 12:46
An Extended Model of Literary Literacyed method in practice. It solves the problem of occupying large storage and low analysis efficiency in areas like the storage of the massive XDR bill, pretreatment, aggregation. It provides valuable references for telecommunication-related researchers and engineering practitioner in respect of using the big data technology.作者: DEFT 時間: 2025-3-30 17:10
Mónika Réti,Edit Lippai,Márk Nemesnce availability is whether the important data keep original value in a composite graph. We analysis the properties of important data of k triangle count, and provide a new method for synthesis graph publication. We show the application of this method in k triangle count, and the experimental results proved the accuracy of the method.作者: 極大的痛苦 時間: 2025-3-30 21:24
https://doi.org/10.1007/978-3-540-78973-4ine-grained emotion analysis method. Combined with TF-IDF and variance statistics, we realized a method of calculating multi-class feature selection. We judge the text whether it is positive or negative first, then choose the fine-grained emotional tendency. And we get good result with the test usin作者: Palpate 時間: 2025-3-31 03:56 作者: Bridle 時間: 2025-3-31 06:44
Practical Modulation Calorimetry was used to reduce the dimension of target features to 1-D, so that PCA output 1-D data can be used as label of support vector machine (SVM). Thus on the premise of not losing the prediction correctness, one model can detect the fault of 2 to 4 features, largely reduce the complexity of model build作者: expository 時間: 2025-3-31 10:50
https://doi.org/10.1007/978-1-4615-3286-6fication framework, thus in low efficiency. Modern GPU has much higher parallelism as well as memory bandwidth than CPU and can be used to accelerate T-overlap query. In this paper, we use hash segmentation to divide inverted lists into segments, then design an efficient inverted index called GHSII 作者: 要控制 時間: 2025-3-31 17:00 作者: persistence 時間: 2025-3-31 19:42
https://doi.org/10.1007/978-1-4615-3286-6y and efficiently. Considering the characteristics of multivariate hydrological time series, the continuity and global features of variables, we proposed a pattern matching method, PP-DTW, which is based on dynamic time warping. In this method, the multivariate time series is firstly segmented, and 作者: 違反 時間: 2025-3-31 22:36 作者: Perineum 時間: 2025-4-1 04:00
https://doi.org/10.1007/978-3-030-93856-7nce twentieth century, but its etiology is not yet completely clear, so it is very important to detect breast cells. In this paper, we built a regression model to detect breast cells, and generated a method for predicting the formation of benign and malignant breast cells by training the model, then作者: Pastry 時間: 2025-4-1 07:39
Master Data of Bill of Material were unavoidable, which directly lead to deficient performance of personalizing. As a significant part of a user’s personal information space, a personal computer owns lots of documents relevant to his or her interest. Therefore, desktop data was introduced to construct a user’s preference model. F
