Results 11 to 20 of about 825,885 (311)
A Non-sequential Representation of Sequential Data for Churn Prediction [PDF]
, 2009 We investigate the length of event sequence giving best predictions\ud when using a continuous HMM approach to churn prediction from sequential\ud data. Motivated by observations that predictions based on only the few most recent\ud events seem to be the most accurate, a non-sequential dataset is constructed\ud from customer event histories by ...
Mark Eastwood, Bogdan Gabrys
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Data Watermarking for Sequential Recommender Systems
Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2In the era of large foundation models, data has become a crucial component in building high-performance AI systems. As the demand for high-quality and large-scale data continues to rise, data copyright protection is attracting increasing attention. In this work, we explore the problem of data watermarking for sequential recommender systems, where a ...
Sixiao Zhang +4 more
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Sequential linked data: The state of affairs [PDF]
Semantic Web, 2021 Sequences are among the most important data structures in computer science. In the Semantic Web, however, little attention has been given to Sequential Linked Data. In previous work, we have discussed the data models that Knowledge Graphs commonly use for representing sequences and showed how these models have an impact on query performance and that ...
Enrico Daga +2 more
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Kernels for sequentially ordered data
CoRR, 2016 We present a novel framework for kernel learning with sequential data of any kind, such as time series, sequences of graphs, or strings. Our approach is based on signature features which can be seen as an ordered variant of sample (cross-)moments; it allows to obtain a "sequentialized" version of any static kernel.
Király, FJ, Oberhauser, H
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Deep Multiview Learning From Sequentially Unaligned Data
IEEE Access, 2020 Multiview learning is concerned with machine learning problems, where data are represented by distinct feature sets or views. Recently, this definition has been extended to accommodate sequential data, i.e., each view of the data is in the form of a ...
Doan Phong Tung, Atsuhiro Takasu
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Data analysis for sequential contingencies under uncertainty
Journal of Big Data, 2023 The existing Z-test for comparing sequential contingencies under classical statistics can be implemented only in the presence of certain frequencies, and the level of significance.
Muhammad Aslam
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An Efficient Method for Mining Top-
IEEE Access, 2020 The problem of exploiting Closed Sequential Patterns (CSPs) is an essential task in data mining, with many different applications. It is used to resolve the situations of huge databases or low minimum support (minsup) thresholds in mining sequential ...
Thi-Thiet Pham +4 more
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Sequential linear regression with online standardized data. [PDF]
PLoS ONE, 2018 The present study addresses the problem of sequential least square multidimensional linear regression, particularly in the case of a data stream, using a stochastic approximation process.
Kévin Duarte +2 more
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Sequential stopping for high-throughput experiments [PDF]
, 2013 In high-throughput experiments, the sample size is typically chosen informally. Most formal sample-size calculations depend critically on prior knowledge.
Müller, Peter, Rossell, David
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Agents for sequential learning using multiple-fidelity data
Scientific Reports, 2022 Sequential learning for materials discovery is a paradigm where a computational agent solicits new data to simultaneously update a model in service of exploration (finding the largest number of materials that meet some criteria) or exploitation (finding ...
Aini Palizhati +5 more
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