Neural Information Processing
27th International Conference, ICONIP 2020, Bangkok, Thailand, November 23–27, 2020, Proceedings, Part I
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Article
Open AccessStromal cells in the tumor microenvironment: accomplices of tumor progression?
The tumor microenvironment (TME) is made up of cells and extracellular matrix (non-cellular component), and cellular components include cancer cells and non-malignant cells such as immune cells and stromal cel...
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Article
Open AccessImplementation of multi-mode nursing insulation program for patients receiving surgery for spine tumor: a propensity score-matched analysis
Spinal tumor surgery usually involved long operation time, large area of soft tissue resection and long wound, and was prone to hypothermia during the operation. Therefore, actively promoting insulation and op...
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Chapter and Conference Paper
KGSynNet: A Novel Entity Synonyms Discovery Framework with Knowledge Graph
Entity synonyms discovery is crucial for entity-leveraging applications. However, existing studies suffer from several critical issues: (1) the input mentions may be out-of-vocabulary (OOV) and may come from a...
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Book and Conference Proceedings
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Book and Conference Proceedings
Neural Information Processing
27th International Conference, ICONIP 2020, Bangkok, Thailand, November 23–27, 2020, Proceedings, Part II
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Book and Conference Proceedings
Neural Information Processing
27th International Conference, ICONIP 2020, Bangkok, Thailand, November 18–22, 2020, Proceedings, Part IV
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Book and Conference Proceedings
Neural Information Processing
27th International Conference, ICONIP 2020, Bangkok, Thailand, November 23–27, 2020, Proceedings, Part III
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Book and Conference Proceedings
Neural Information Processing
27th International Conference, ICONIP 2020, Bangkok, Thailand, November 18–22, 2020, Proceedings, Part V
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Chapter
Deep Learning and Its Applications to Natural Language Processing
Natural language processing (NLP), utilizing computer programs to process large amounts of language data, is a key research area in artificial intelligence and computer science. Deep learning technologies have...
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Article
Implicit Heterogeneous Features Embedding in Deep Knowledge Tracing
Deep recurrent neural networks have been successfully applied to knowledge tracing, namely, deep knowledge tracing (DKT), which aims to automatically trace students’ knowledge states by mining their exercise p...
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Chapter and Conference Paper
A Broad Neural Network Structure for Class Incremental Learning
Class Incremental Learning, learning concepts over time, is a promising research topic. Due to unknowing the number of output classes, researchers have to develop different methods to model new classes while p...
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Chapter and Conference Paper
Neural Machine Translation for Financial Listing Documents
In this paper, we focus on develo** a Neural Machine Translation (NMT) system on English-to-Traditional-Chinese translation for financial prospectuses of companies which seek listing on the Hong Kong Stock E...
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Chapter and Conference Paper
Heterogeneous Features Integration in Deep Knowledge Tracing
Knowledge tracing is a significant research topic in educational data mining. The goal is to automatically trace students’ knowledge states by analyzing their exercise performance. Recently proposed Deep Knowl...
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Chapter and Conference Paper
Non-monotonic Feature Selection for Regression
Feature selection is an important research problem in machine learning and data mining. It is usually constrained by the budget of the feature subset size in practical applications. When the budget changes, th...
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Chapter and Conference Paper
Ensemble Learning for Imbalanced E-commerce Transaction Anomaly Classification
This paper presents the main results of our on-going work, one month before the deadline, on the 2009 UC San Diego data mining contest. The tasks of the contest are to rank the samples in two e-commerce transa...
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Chapter and Conference Paper
Sprinkled Latent Semantic Indexing for Text Classification with Background Knowledge
In text classification, one key problem is its inherent dichotomy of polysemy and synonym; the other problem is the insufficient usage of abundant useful, but unlabeled text documents. Targeting on solving the...
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Chapter and Conference Paper
Outliers Treatment in Support Vector Regression for Financial Time Series Prediction
Recently, the Support Vector Regression (SVR) has been applied in the financial time series prediction. The financial data are usually highly noisy and contain outliers. Detecting outliers and deflating their ...
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Chapter
Improving Chow-Liu Tree Performance by Mining Association Rules
We present a novel approach to construct a kind of tree belief network, in which the “nodes” are subsets of variables of dataset. We call this model Large Node Chow-Liu Tree (LNCLT). This technique uses the co...
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Chapter
Financial Time Series Prediction Using Non-fixed and Asymmetrical Margin Setting with Momentum in Support Vector Regression
Recently, Support Vector Regression (SVR) has been applied to financial time series prediction. The financial time series usually contains the characteristics of small sample size, high noise and non-stationar...
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Chapter and Conference Paper
Support Vector Machine Regression for Volatile Stock Market Prediction
Recently, Support Vector Regression (SVR) has been introduced to solve regression and prediction problems. In this paper, we apply SVR to financial prediction tasks. In particular, the financial data are usual...
