针对Top-k高效用项集挖掘算法在挖掘过程中忽略内存管理的问题,提出基于DBP的Top-k高效用项集挖掘算法TKBPH(Top-k buffer pool high utility itemsets mining),采用数... 蒋华,路昕宇,王慧娇,... - 《计算机工程与设计》 被引量: 0发表: 2021年
Ejaculated bovine spermatozoa retain a pool of RNAs that may have a function in early embryogenesis and be used as predictors of male fertility. The bovine... CJ Card,EJ Anderson,S Zamberlan,... - 《Biology of Reproduction》 被引量: 52发表: 2013年 Conference v2.0: An Uncertain Version of...
Most previous studies focus on how to help customers find a set of "best" possible products from a pool of given products. In this paper, we identify an interesting problem, finding top-k preferable products, which has not been studied before. Given a set of products in the existing ...
() for pool in self.pools: pool.reset_parameters() self.lin1.reset_parameters() self.lin2.reset_parameters() def forward(self, data): x, edge_index, batch = data.x, data.edge_index, data.batch x = F.relu(self.conv1(x, edge_index)) xs = [global_mean_pool(x, batch)] for ...
We define and analyze the Fair Top-k Ranking problem with multiple protected groups, in which we want to determine a subset of k candidates from a large pool of n≫k candidates, in a way that maintains high utility (selects the “best” candidates from each group), subject to a group...
The novel disseminated framework for pooled location based information inception and sharing, considering the development in internet application and location access in mobile devices. It allows the versatile clients to impart their involvement with a wide range of points of interests (POI). The ...
As the pool of attributes for selection by individual queries may be large, the data are indexed with per-attribute sorted lists, and a threshold algorithm (TA) is applied on the lists involved in each query. The TA executes in two phases鈥攆ind a cut-off threshold for the top- k ...
在OLAP场景,排序是一个非常重要的功能。也是衡量数据库是否适合OLAP场景的一个重要指标。例如这些场景: 1、求TOP-K,例如在对数据进行分组后,取出每个分组的TOP-K。 2、求中位数,要求对数据排序,并取出处于中间水位的值。 3、数据柱状图,需要对数据进行排序,并按记录均匀分割成若干BUCKET,获得bucket边界。
因此本文提出数据缓冲池(databufferpool,DBP)结构的高效用项集挖掘算法TKBPH。算法将效用链表存储在数据缓冲池并由索引链表记录其位置,挖掘过程中通过直接访问索引链表读取效用链表位置,在数据缓冲池动态插入和删除效用链表,降低内存空间消耗,提升算法效率。相关定义及问题陈述设由m个项组成的项集I={i1,i2,i3,…,im...
Constraint-based data mining [24] has been widely used for finding frequent items or patterns in a given pool of data [17,18]. Various types of constraints can be used in mining, such as knowledge type constraints, data constraints, dimension constraints, interestingness constraints, rule constra...