標(biāo)題: Titlebook: Data Warehousing and Knowledge Discovery; 9th International Co Il Yeal Song,Johann Eder,Tho Manh Nguyen Conference proceedings 2007 Springe [打印本頁] 作者: 獨(dú)裁者 時(shí)間: 2025-3-21 18:48
書目名稱Data Warehousing and Knowledge Discovery影響因子(影響力)
書目名稱Data Warehousing and Knowledge Discovery影響因子(影響力)學(xué)科排名
書目名稱Data Warehousing and Knowledge Discovery網(wǎng)絡(luò)公開度
書目名稱Data Warehousing and Knowledge Discovery網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Data Warehousing and Knowledge Discovery被引頻次
書目名稱Data Warehousing and Knowledge Discovery被引頻次學(xué)科排名
書目名稱Data Warehousing and Knowledge Discovery年度引用
書目名稱Data Warehousing and Knowledge Discovery年度引用學(xué)科排名
書目名稱Data Warehousing and Knowledge Discovery讀者反饋
書目名稱Data Warehousing and Knowledge Discovery讀者反饋學(xué)科排名
作者: 物種起源 時(shí)間: 2025-3-22 00:04 作者: Surgeon 時(shí)間: 2025-3-22 04:20 作者: PLAYS 時(shí)間: 2025-3-22 08:18 作者: flammable 時(shí)間: 2025-3-22 12:36 作者: 故意 時(shí)間: 2025-3-22 13:33
A Dynamic View Materialization Scheme for Sequences of Query and Update Statementspically, the workload is a set of queries and updates. In many applications, the workload statements come in a fixed order. This scenario provides additional opportunities for optimization. Further, it modifies the view selection problem to one where views are materialized dynamically during the wor作者: 故意 時(shí)間: 2025-3-22 18:11 作者: 是限制 時(shí)間: 2025-3-22 23:53
Computing Join Aggregates over Private Tableshare aggregated information over the join of their tables, but want to conceal the details that generate such information. The join operation presents a challenge to privacy preservation because it requires matching individual records from private tables. We solve this problem by a novel sketching p作者: 虛弱 時(shí)間: 2025-3-23 03:58 作者: Banquet 時(shí)間: 2025-3-23 07:03 作者: 秘方藥 時(shí)間: 2025-3-23 10:40
OLAP Technology for Business Process Intelligence: Challenges and Solutionsousing and mining technologies. However, the differences in the underlying assumptions and objectives of the business process model and the multidimensional data model aggravate a straightforward solution for a meaningful convergence of the two concepts..This paper presents the results of an ongoing作者: 不能平靜 時(shí)間: 2025-3-23 17:11
Built-In Indicators to Automatically Detect Interesting Cells in a Cubehile exploring the cube, analysts are rapidly confronted by analyzing a huge number of visible cells to identify the most interesting ones. Coupling OLAP technologies and mining methods may help them by the automation of this tedious task. In the scope of discovery-driven exploration, this paper pre作者: 分散 時(shí)間: 2025-3-23 20:07 作者: saphenous-vein 時(shí)間: 2025-3-24 00:03 作者: COST 時(shí)間: 2025-3-24 06:24 作者: LAST 時(shí)間: 2025-3-24 09:38 作者: 拒絕 時(shí)間: 2025-3-24 13:23 作者: 松緊帶 時(shí)間: 2025-3-24 18:40
Integrating Clustering Data Mining into the Multidimensional Modeling of Data Warehouses with UML PrDWs) can help users to analyze stored data, because they contain preprocessed data for analysis purposes. Furthermore, the . (MD) model of DWs, intuitively represents the system underneath. However, most of the clustering data mining are applied at a low-level of abstraction to complex unstructured 作者: Torrid 時(shí)間: 2025-3-24 21:50
A UML Profile for Representing Business Object States in a Data Warehousested in the states of these business objects: A customer is either a potential customer, a first time customer, a regular customer or a past customer; purchase orders may be pending or fullfilled..Business objects and their states can be distributed over many parts of the DWH, and appear in measures作者: Ergots 時(shí)間: 2025-3-25 00:43 作者: 歪曲道理 時(shí)間: 2025-3-25 03:46
Daniel Wesierski,Sebastian Cygertmodeled as a graph that is annotated with policies for the management of evolution events. Given a change at an element of the graph, our method detects the parts of the graph that are affected by this change and indicates the way they are tuned to respond to it.作者: Lime石灰 時(shí)間: 2025-3-25 09:58 作者: 修改 時(shí)間: 2025-3-25 14:56 作者: Entropion 時(shí)間: 2025-3-25 19:37
Allen Newell,Cliff Shaw,Herbert Simon. Such a measure returns the number of trajectories that lie in a spatial region during a given temporal interval. We devise a novel way to compute an approximate, but very accurate, presence aggregate function, which algebraically combines a bounded amount of measures stored in the base cells of the data cube.作者: 沉著 時(shí)間: 2025-3-25 22:53 作者: 捕鯨魚叉 時(shí)間: 2025-3-26 02:45 作者: 聽寫 時(shí)間: 2025-3-26 05:44 作者: GEON 時(shí)間: 2025-3-26 09:43
https://doi.org/10.1007/978-3-662-00807-2available not only for the relational tables themselves, but also for the associated r-tree indexes. Experimental results demonstrate compression rates of more than 90% for multi-dimensional data, and up to 98% for the indexes.作者: Biguanides 時(shí)間: 2025-3-26 13:02
Daniel Wesierski,Sebastian Cygerton. The objective is to avoid waiting for a new workload from the updated DW model. We propose to maintain existing queries coherent and create new queries to deal with probable future analysis needs.作者: 江湖郎中 時(shí)間: 2025-3-26 18:41 作者: FLORA 時(shí)間: 2025-3-26 23:56 作者: LIKEN 時(shí)間: 2025-3-27 01:39
https://doi.org/10.1007/978-3-322-83906-0process. Our knowledge induction approach is based on rough set theory. We present the knowledge induction algorithm driven by a user’s query and explain the method through running examples. The advantages of the proposed techniques are confirmed with experimental results.作者: 殺人 時(shí)間: 2025-3-27 08:46 作者: 祖?zhèn)髫?cái)產(chǎn) 時(shí)間: 2025-3-27 13:28
A Hilbert Space Compression Architecture for Data Warehouse Environmentsavailable not only for the relational tables themselves, but also for the associated r-tree indexes. Experimental results demonstrate compression rates of more than 90% for multi-dimensional data, and up to 98% for the indexes.作者: 微枝末節(jié) 時(shí)間: 2025-3-27 14:26
Evolution of Data Warehouses’ Optimization: A Workload Perspectiveon. The objective is to avoid waiting for a new workload from the updated DW model. We propose to maintain existing queries coherent and create new queries to deal with probable future analysis needs.作者: Reverie 時(shí)間: 2025-3-27 19:37 作者: Infiltrate 時(shí)間: 2025-3-27 22:40
Automating the Schema Matching Process for Heterogeneous Data Warehousestions for aggregation level matching, which builds the most complex part of the process. A software implementation of the entire process is provided in order to perform its verification, as well as to determine the proper selection metric for mapping different multidimensional structures.作者: 自作多情 時(shí)間: 2025-3-28 03:44
Semantic Knowledge Integration to Support Inductive Query Optimizationprocess. Our knowledge induction approach is based on rough set theory. We present the knowledge induction algorithm driven by a user’s query and explain the method through running examples. The advantages of the proposed techniques are confirmed with experimental results.作者: 協(xié)奏曲 時(shí)間: 2025-3-28 10:17
An OLAM-Based Framework for Complex Knowledge Pattern Discovery in Distributed-and-Heterogeneous-Dat a formal model underlying this framework, called ...), and a reference architecture for such a framework. Another contribute of our work is represented by the proposal of ., a visual tool that supports the editing of even-complex KDD processes according to the guidelines drawn by ...作者: Shuttle 時(shí)間: 2025-3-28 11:20 作者: Hamper 時(shí)間: 2025-3-28 15:29
Chao Yang,Haiyan Chen,Sheng Liu,Sheng Malicit in existing conceptual models. We identify a need to make this relationship more accessible..We introduce the .. It makes the relationship between the business objects and the DWH conceptually visible. The UML Profile is applied to an example.作者: Vasoconstrictor 時(shí)間: 2025-3-28 19:16 作者: neutralize 時(shí)間: 2025-3-29 02:00
A UML Profile for Representing Business Object States in a Data Warehouselicit in existing conceptual models. We identify a need to make this relationship more accessible..We introduce the .. It makes the relationship between the business objects and the DWH conceptually visible. The UML Profile is applied to an example.作者: 你正派 時(shí)間: 2025-3-29 05:47
Spatio-temporal Aggregations in Trajectory Data Warehouses. Such a measure returns the number of trajectories that lie in a spatial region during a given temporal interval. We devise a novel way to compute an approximate, but very accurate, presence aggregate function, which algebraically combines a bounded amount of measures stored in the base cells of the data cube.作者: 慷慨援助 時(shí)間: 2025-3-29 09:50 作者: 中古 時(shí)間: 2025-3-29 13:20 作者: chuckle 時(shí)間: 2025-3-29 19:18
A Clustered Dwarf Structure to Speed Up Queries on Data Cubes facilitate the implementation, we design a partition strategy and a logical clustering mechanism. Experimental results show our methods can effectively improve the query performance on data cubes, and the recursion clustering method is suitable for both point queries and range queries.作者: oncologist 時(shí)間: 2025-3-29 20:19 作者: NAV 時(shí)間: 2025-3-30 00:32 作者: constitutional 時(shí)間: 2025-3-30 07:40
Linear periodic operators and systemsng or as a querying tool, helping the user in selecting the mostly preferred items. Performance evaluation based on different distributions, populations and dimensionalities show the effectiveness of the proposed scheme.作者: brother 時(shí)間: 2025-3-30 11:52 作者: Incise 時(shí)間: 2025-3-30 13:56 作者: 致敬 時(shí)間: 2025-3-30 19:28 作者: 衰老 時(shí)間: 2025-3-30 21:31 作者: endarterectomy 時(shí)間: 2025-3-31 03:50 作者: 是限制 時(shí)間: 2025-3-31 05:53
Integrating Clustering Data Mining into the Multidimensional Modeling of Data Warehouses with UML Prn top of the MD model of a DW. This will allow us to avoid the duplication of the time-consuming preprocessing stage and simplify the clustering design on top of DWs improving the discovery of knowledge.作者: Femine 時(shí)間: 2025-3-31 11:07
Conference proceedings 2007test research issues and experiences in developing and deploying data warehousing and knowledge d- covery systems, applications, and solutions. This year’s conference, the Ninth Inter- tional Conference on Data Warehousing and Knowledge Discovery (DaWaK 2007), built on this tradition of facilitating作者: 培養(yǎng) 時(shí)間: 2025-3-31 16:42 作者: 愉快么 時(shí)間: 2025-3-31 17:43 作者: 全神貫注于 時(shí)間: 2025-3-31 22:28
Daniel Wesierski,Sebastian Cygerte abstract software modules, queries, reports and views as (sequences of) queries in SQL enriched with functions. Queries and relations are uniformly modeled as a graph that is annotated with policies for the management of evolution events. Given a change at an element of the graph, our method detec
