Multi-dimensional data modellingData warehousingOnline analytical processing (OLAPTourism knowledge destinationThe travel and tourism domain as a global competitive service business has a special need to unders
Integration of Data Mining Results into Multi-dimensional Data Models Presentation This paper presents emerging trends in the area of temporal abstraction and data mining, as applied to multi-dimensional data. The clinical context is that... V Meyer,W Hpken,M Fuchs,... 被引量: 0发表: 2016年...
Attempts to predict bankruptcy have involved the application of data mining techniques to credit card data. This is a difficult problem, since credit card data is multi-dimensional, consisting of monthly account records and daily transaction records. In this paper, we describe a two-stage approach...
The richness of information contained in raster data is only limited by the number of captured bands and its resolution. To derive the full benefits by processing such data it has become of utmost importance to overhaul existing multi-dimensional approaches and consider the geospatial characteristic o...
3) High-dimensional data mining 高维数据挖掘 例句>> 4) multimedia data mining 多媒体数据挖掘 1. Clustering is one of the focused problems in multimedia data mining,and similarity measurement among data is fundamental to clustering. 聚类是多媒体数据挖掘的重要任务之一,数据之间的相似性度量是聚类...
Our study identifies reference-free ‘absolute’ feature quantification as the root cause of irreproducibility in multi-omics measurement and data integration and establishes the advantages of ratio-based multi-omics profiling with common reference materials....
Mühlbacher’s TreePOD system emphasizes the visual exploration of a two-dimensional Pareto front of decision trees. Some approaches load off most of the construction work to the user (Ankerst, Ester, Kriegel, 2000, Han, Cercone, 2002). More similar to our approach is “constraint-based ...
Multi-dimensional interpolators High dimension model reduction (HDMR) Morse-Smale complex Model capabilities Data Post-Processing capabilities Data clustering Data regression Data dimensionality Reduction Custom generic post-processors Time-dependent data analysis (statistics, clustering and time warping metrics)...
Deep learning techniques have proven to be effective in solving the facial emotion recognition (FER) problem. However, it demands a significant amount of supervision data which is often unavailable due to privacy and ethical concerns. In this paper, we p
Section 4 describes the proposed multi-dimensional relation model. Section 5 presents the evaluation results for VAI prediction. Lastly, conclusions are drawn in Section 6. 2. Related work 2.1. Dimensional sentiment resources The affective norms for English words (ANEW) is the first three-...