Mingyang Xu

Works (4)

Updated: July 5th, 2023 15:36

2018 article

An Intelligent and Hybrid Weighted Fuzzy Time Series Model Based on Empirical Mode Decomposition for Financial Markets Forecasting

ADVANCES IN DATA MINING: APPLICATIONS AND THEORETICAL ASPECTS (ICDM 2018), Vol. 10933, pp. 104–118.

By: R. Yang n , J. He*, M. Xu n, H. Ni n, P. Jones n & N. Samatova*

Contributors: R. Yang n , J. He*, M. Xu n, H. Ni n, P. Jones n & N. Samatova*

author keywords: EMD; Weighted fuzzy time series; Human learning optimization algorithm; Financial markets forecasting
TL;DR: A new Intelligent Hybrid Weighted Fuzzy (IHWF) time series model to improve forecasting accuracy in financial markets, which are complex nonlinear time-sensitive systems, influenced by many factors. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: June 17, 2019

2018 article

Mining Aspect-Specific Opinions from Online Reviews Using a Latent Embedding Structured Topic Model

COMPUTATIONAL LINGUISTICS AND INTELLIGENT TEXT PROCESSING, CICLING 2017, PT II, Vol. 10762, pp. 195–210.

By: M. Xu n, R. Yang n , P. Jones n & N. Samatova*

Contributors: M. Xu n, R. Yang n , P. Jones n & N. Samatova*

TL;DR: This paper proposes a Latent embedding structured Opinion mining Topic model, called the LOT, which can simultaneously discover relevant aspect-level specific opinions from small or large numbers of reviews and to assign accurate sentiment to words. (via Semantic Scholar)
UN Sustainable Development Goals Color Wheel
UN Sustainable Development Goal Categories
1. No Poverty (OpenAlex)
Sources: Web Of Science, ORCID
Added: January 28, 2019

2017 article

A Lifelong Learning Topic Model Structured Using Latent Embeddings

2017 11TH IEEE INTERNATIONAL CONFERENCE ON SEMANTIC COMPUTING (ICSC), pp. 260–261.

By: M. Xu n, R. Yang n , S. Harenberg n & N. Samatova n

Contributors: M. Xu n, R. Yang n , S. Harenberg n & N. Samatova n

author keywords: Lifelong learning; Topic modeling; Latent embeddings
TL;DR: A latent-embedding-structured lifelong learning topic model, called the LLT model, to discover coherent topics from a corpus and exploit latent word embeddings to structure the model and mine word correlation knowledge to assist in topic modeling. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: August 6, 2018

2017 article

An Intelligent Weighted Fuzzy Time Series Model Based on a Sine-Cosine Adaptive Human Learning Optimization Algorithm and Its Application to Financial Markets Forecasting

ADVANCED DATA MINING AND APPLICATIONS, ADMA 2017, Vol. 10604, pp. 595–607.

By: R. Yang n , M. Xu n, J. He*, S. Ranshous n & N. Samatova*

Contributors: R. Yang n , M. Xu n, J. He*, S. Ranshous n & N. Samatova*

author keywords: Weighted fuzzy time series; Human learning optimization algorithm; Financial markets forecasting
TL;DR: An intelligent weighted fuzzy time series model for financial forecasting, which uses a sine-cosine adaptive human learning optimization (SCHLO) algorithm to search for the optimal parameters for forecasting, is presented. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: November 26, 2018

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