252 research outputs found
Controlling False Positives in Association Rule Mining
Association rule mining is an important problem in the data mining area. It
enumerates and tests a large number of rules on a dataset and outputs rules
that satisfy user-specified constraints. Due to the large number of rules being
tested, rules that do not represent real systematic effect in the data can
satisfy the given constraints purely by random chance. Hence association rule
mining often suffers from a high risk of false positive errors. There is a lack
of comprehensive study on controlling false positives in association rule
mining. In this paper, we adopt three multiple testing correction
approaches---the direct adjustment approach, the permutation-based approach and
the holdout approach---to control false positives in association rule mining,
and conduct extensive experiments to study their performance. Our results show
that (1) Numerous spurious rules are generated if no correction is made. (2)
The three approaches can control false positives effectively. Among the three
approaches, the permutation-based approach has the highest power of detecting
real association rules, but it is very computationally expensive. We employ
several techniques to reduce its cost effectively.Comment: VLDB201
A Flexible Approach to Finding Representative Pattern Sets
10.1109/TKDE.2013.27IEEE Transactions on Knowledge and Data Engineerin
Mao-Zedong At SemEval-2023 Task 4: Label Represention Multi-Head Attention Model With Contrastive Learning-Enhanced Nearest Neighbor Mechanism For Multi-Label Text Classification
The study of human values is essential in both practical and theoretical
domains. With the development of computational linguistics, the creation of
large-scale datasets has made it possible to automatically recognize human
values accurately. SemEval 2023 Task 4\cite{kiesel:2023} provides a set of
arguments and 20 types of human values that are implicitly expressed in each
argument. In this paper, we present our team's solution. We use the
Roberta\cite{liu_roberta_2019} model to obtain the word vector encoding of the
document and propose a multi-head attention mechanism to establish connections
between specific labels and semantic components. Furthermore, we use a
contrastive learning-enhanced K-nearest neighbor
mechanism\cite{su_contrastive_2022} to leverage existing instance information
for prediction. Our approach achieved an F1 score of 0.533 on the test set and
ranked fourth on the leaderboard
“Reporting or Interpreting?”—A Discoursal Study of Broadcasts on NBA Games in China
From the perspective of empirical discourse analysis, this paper identifies the site broadcasters’ roles and cognitive blending process in NBA (National Basketball Association) broadcasts in China. The authors find that NBA broadcasters chiefly interpret the information they have obtained from sports sites and interviews with the coaches and players, employing various interpreting strategies, such as commentary, amplification, supplementation and restructure. Cognitively, the language that NBA broadcasters applied reveals their cognitive blending process of interpreting techniques, strategies, sports knowledge and attitudes towards the games, of who take up different roles to fulfill different communicating purposes, all of which project various cognitions on NBA games. Despite the fact that one role might make certain linguistic behaviors prevail over the others, especially their interpreting role, NBA site broadcasters coordinate it with other roles properly through which they present different levels of translational and constructional schematicity, thus yielding a coherent and constructional working mode of NBA broadcasting practice in China
Invisible nanowires with interfering electric and toroidal dipoles
By studying the scattering of normally incident plane waves by a single nanowire, we reveal the indispensable role of toroidal multipole excitation in multipole expansions of radiating sources. It is found that for both p-polarized and s-polarized incident waves, toroidal dipoles can be effectively excited within homogenous dielectric nanowires in the optical spectrum regime. We further demonstrate that the plasmonic core–shell nanowires can be rendered invisible through destructive interference of the electric and toroidal dipoles, which may inspire many nano-wire-based light–matter interaction studies, and incubate biological and medical applications that require non-invasive detections and measurements
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