Works (16)
Updated: July 5th, 2023 15:40
2022 journal article
Context-Based Identification of Muscle Invasion Status in Patients With Bladder Cancer Using Natural Language Processing
JCO Clinical Cancer Informatics.
MeSH headings : Cystectomy / methods; Female; Humans; Male; Muscles / pathology; Natural Language Processing; Rare Diseases; Urinary Bladder Neoplasms / pathology; Urologic Surgical Procedures
TL;DR:
This NLP model, with high accuracy, may be a practical tool for efficiently identifying BC invasion status and aid in population-based BC research.
(via Semantic Scholar)
Source: ORCID
Added: July 30, 2022
2022 journal article
Identification of Patients With Metastatic Prostate Cancer With Natural Language Processing and Machine Learning
JCO Clinical Cancer Informatics.
MeSH headings : Algorithms; Electronic Health Records; Humans; Machine Learning; Male; Natural Language Processing; Prostatic Neoplasms / diagnosis
TL;DR:
This population-level NLP model for identifying patients with mPCa was more accurate than using ICD9/10 billing codes when compared with chart-reviewed data and an International Classification of Diseases 9/10 code-based method.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education
(OpenAlex)
Source: ORCID
Added: October 11, 2022
2021 book
Continuous Human Learning Optimization with Enhanced Exploitation
In Communications in Computer and Information Science (pp. 472–487).
Contributors: L. Wang *, B. Huang *, X. Wu * & n
Source: ORCID
Added: December 6, 2021
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.
Contributors: 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.
Contributors: M. Xu n, 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 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.
Contributors: M. Xu n, 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.
Contributors: 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
2017 conference paper
Leveraging External Knowledge for Phrase-Based Topic Modeling
Proceedings - 2017 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2017, 29–32.
Contributors: M. Xu n, n , S. Ranshous n, S. Li n & N. Samatova n
TL;DR:
Experimental results show that the proposed knowledge-based topic model outperforms the state-of-the-art baseline on both small and large datasets, extracting more meaningful phrases and coherent topics.
(via Semantic Scholar)
Sources: ORCID, NC State University Libraries
Added: August 6, 2018
2017 conference paper
Real time utility-based recommendation for revenue optimization via an adaptive online Top-K high utility itemsets mining model
ICNC-FSKD 2017 - 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, 1859–1866.
Contributors: n , M. Xu n, P. Jones n & N. Samatova*
TL;DR:
This work considers that online transaction streams are usually accompanied with flow fluctuation, and proposes an Adaptive Online Top-K (RAOTK) high utility itemsets mining model to guide the utility-based recommendations.
(via Semantic Scholar)
Sources: ORCID, NC State University Libraries
Added: August 6, 2018
2015 journal article
A human learning optimization algorithm and its application to multi-dimensional knapsack problems
APPLIED SOFT COMPUTING, 34, 736–743.
Contributors: L. Wang *, n , H. Ni*, W. Ye *, M. Fei * & P. Pardalos *
author keywords: Human learning optimization; Meta-heuristic; Multi-dimensional knapsack problem; Global optimization
TL;DR:
Four learning operators inspired by the human learning process are developed and the presented HLO achieves the best performance in comparison with other meta-heuristics, which demonstrates that HLO is a promising optimization tool.
(via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: August 6, 2018
2015 journal article
An adaptive simplified human learning optimization algorithm
Information Sciences, 320, 126–139.
Contributors: L. Wang *, H. Ni*, * , P. Pardalos *, X. Du * & M. Fei *
author keywords: Human learning optimization; Meta-heuristic; Global optimization; Social learning; Individual learning
TL;DR:
The experimental results demonstrate that the developed ASHLO significantly outperforms BPSO, MBDE, bFOA and ABHS and has a robust search ability for various problems.
(via Semantic Scholar)
Source: ORCID
Added: December 6, 2021
2015 journal article
Intelligent virtual reference feedback tuning and its application to heat treatment electric furnace control
Engineering Applications of Artificial Intelligence, 46, 1–9.
Contributors: L. Wang *, H. Ni*, * , P. Pardalos *, L. Jia * & M. Fei *
author keywords: Intelligent virtual reference feedback tuning; VRFT; Harmony search; Ant colony optimization; Heat treatment electric furnace; Data-driven
TL;DR:
A novel intelligent VRFT (IVRFT) based on adaptive binary ant system harmony search (ABASHS) where the reference model of VRFT, which potentially determines the control performance, is coordinately optimized with the controller by ABASHS to achieve the best control performance.
(via Semantic Scholar)
Source: ORCID
Added: December 6, 2021
2014 book
A simple human learning optimization algorithm
In Communications in Computer and Information Science (Vol. 462, pp. 56–65).
TL;DR:
Considering the ease of implementation and the excellence of global search ability, SHLO is a promising optimization tool.
(via Semantic Scholar)
Source: ORCID
Added: December 6, 2021
2013 journal article
An adaptive fuzzy controller based on harmony search and its application to power plant control
International Journal of Electrical Power and Energy Systems, 53(1), 272–278.
Contributors: L. Wang *, * , P. Pardalos *, L. Qian & M. Fei *
author keywords: Adaptive fuzzy control; Harmony search; Power plant; Binary Harmony Search
TL;DR:
The experimental results demonstrate that ABHSAFC can implement the expected non-overshoot control efficiently and outperforms the classical Lyapunov-based adaptive fuzzy control, AB HS-based fuzzy control and ABHS-based PID control.
(via Semantic Scholar)
Source: ORCID
Added: December 6, 2021
2013 journal article
An improved adaptive binary Harmony Search algorithm
Information Sciences, 232, 58–87.
Contributors: L. Wang *, * , Y. Xu *, Q. Niu *, P. Pardalos * & M. Fei *
author keywords: Harmony Search; Binary Harmony Search; Meta-heuristic; Knapsack problem
TL;DR:
An improved adaptive binary Harmony Search (ABHS) algorithm is proposed in this paper to solve the binary-coded problems more effectively and outperforms the binary Harmony search algorithm, the novel global Harmony Search algorithm and the discrete binary Particle Swarm Optimization in terms of the search accuracy and convergence speed.
(via Semantic Scholar)
Source: ORCID
Added: December 6, 2021
2013 journal article
Feature selection based on meta-heuristics for biomedicine
Optimization Methods and Software, 29(4), 703–719.
Contributors: L. Wang *, H. Ni*, * , V. Pappu*, M. Fenn* & P. Pardalos *
author keywords: meta-heuristic; feature selection; biomedicine
TL;DR:
Six meta-heuristics, that is, a genetic algorithm, particle swarm optimization, ant colony optimization, harmony search, differential evolution, and quantum-inspired evolutionary algorithm, are introduced into feature selection and the performance of the algorithms is analysed and compared with each other for solving feature selection in biomedicine effectively.
(via Semantic Scholar)
Source: ORCID
Added: December 6, 2021
Employment
Updated: March 5th, 2018 23:54
2017 - present
North Carolina State University Raleigh, NC, US
Research Assistant
Computer Science
2014 - 2016
North Carolina State University Raleigh, NC, US
Teaching Assistant
Computer Science
Education
Updated: March 5th, 2018 23:52
2014 - present
North Carolina State University Raleigh, NC, US
Computer Science
2007 - 2014
Shanghai University Shanghai, Shanghai, CN
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