Huawei Technologies Co., Limited

Huawei Cloud Computing Technologies Co., Ltd.

Michael Chih Hung Li

Zanqing Zhang

Haolin Guo

Roozbeh Jalali

Wen Qing Chen

Sundar Annamalai

Fatemeh Mansour Kiaie

Ahmed Helal

Computer-implemented methods and computing systems for reorganizing data are disclosed. One or more user defined functions (UDFs) are applied to one or more columns of a data set to generate a hidden column. The data set partitioned according to a first partition scheme and the hidden column are stored in memory of a computing system. A set of queries run against the data set and the hidden column are stored in the memory. Each query in the set of queries and the one or more UDFs are processed with a machine learning model to select a second partition scheme for the data set. The data set in the memory is reorganized according to the second partition scheme.

Computer-implemented methods and computing systems for reorganizing data

There is provided a method for embedding a digital watermark into and extracting a digital watermark from a numerical data set. In accordance with embodiments of the present disclosure, there is provided a method for embedding a digital watermark into a numerical data set. The method includes selecting portions of the numerical data set identified as data noise, the selected portions to be used for embedding the digital watermark into the numerical data set, the digital watermark being unique for each recipient of the numerical data. The method further includes replacing the least significant bit (LSB) of at least some of the selected portions of the numerical data set with at least portion of the digital watermark.

Method and apparatus for embedding and extracting digital watermarking for numerical data

Methods and system for embedding digital watermark information into textual data arranged in a table of cells are provided. A first subset of cells are selected and for each primary cell key and cell partition number are determined. A portion of a digital watermark ID code is embedded at an embedding position determined based on the partition number. Methods and systems for extracting digital watermark information from the textual data are also provided. A cell is fetched from the table and the presence of portion of the digital watermark ID code is determined. A primary cell key and cell partition number are determined. A portion of the digital watermark ID code is extracted at the embedding position within the cell, the embedding position determined based on the cell partition number. The digital watermarking systems and methods provide tracking for unauthorized copying of the data while modifying only a subset of the data.

Digital watermarking for textual data

A method and a system of using machine learning to automatically generate a reference data structure for a K-anonymity model. A vector space is generated from reference text data, where the vector space is defined by numerical vectors representative of semantic meanings of the reference text words. Input text words are converted into numerical vectors using the vector space. Word clusters are formed according to semantic similarity between the input text words, where the semantic similarity between pairs of input text words is represented by metric values determined from pairs of numerical vectors. The word clusters define nodes of the reference data structure. A text label is applied to each node of the reference data structure, where the text label is representative of the semantic meaning shared by elements of the word cluster.

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Markham, Canada

Michael Chih Hung Li