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Special Topic on environment and sustainable development

Frontiers of Chemical Science and Engineering 2017, Volume 11, Issue 3, Pages 291-292 doi: 10.1007/s11705-017-1667-6

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Emerging topic identification from app reviews via adaptive online biterm topic modeling Research Article

Wan ZHOU, Yong WANG, Cuiyun GAO, Fei YANG,yongwang@ahpu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 5, Pages 678-691 doi: 10.1631/FITEE.2100465

Abstract: Emerging topics in highlight the topics (e.g., software bugs) with which users are concerned during certain periods. Identifying emerging topics accurately, and in a timely manner, could help developers more effectively update apps. Methods for identifying emerging topics in based on s or clustering methods have been proposed in the literature. However, the accuracy of is reduced because reviews are short in length and offer limited information. To solve this problem, an improved (IETI) approach is proposed in this work. Specifically, we adopt techniques to reduce noisy data, and identify emerging topics in using the adaptive online biterm . Then we interpret the implicature of emerging topics through relevant phrases and sentences. We adopt the official app changelogs as ground truth, and evaluate IETI in six common apps. The experimental results indicate that IETI is more accurate than the baseline in identifying emerging topics, with improvements in the F1 score of 0.126 for phrase labels and 0.061 for sentence labels. Finally, we release the codes of IETI on Github (https://github.com/wanizhou/IETI).

Keywords： App reviews Emerging topic identification Topic model Natural language processing

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Topic discovery and evolution in scientific literature based on content and citations Article

Hou-kui ZHOU, Hui-min YU, Roland HU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 10, Pages 1511-1524 doi: 10.1631/FITEE.1601125

Abstract: document citation relations and the con-tent of the document itself via a probabilistic generative modelThe citation-content-LDA topic model exploits a two-level topic model that includes the citation informationThe model parameters are estimated by a collapsed Gibbs sampling algorithm.We also propose a topic evolution algorithm that runs in two steps: topic segmentation and topic dependencyWe have tested the proposed citation-content-LDA model and topic evolution algorithm on two online datasets

Keywords： Topic extraction Topic evolution Evaluation method

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Supervised topic models with weighted words: multi-label document classification None

Yue-peng ZOU, Ji-hong OUYANG, Xi-ming LI

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 4, Pages 513-523 doi: 10.1631/FITEE.1601668

Abstract: Supervised topic modeling algorithms have been successfully applied to multi-label document classificationExperimental results demonstrate that CF-weight based algorithms are competitive with the existing supervised topic

Keywords： Supervised topic model Multi-label classification Class frequency Labeled latent Dirichlet allocation

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Personalized topic modeling for recommending user-generated content Article

Wei ZHANG, Jia-yu ZHUANG, Xi YONG, Jian-kou LI, Wei CHEN, Zhe-min LI

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 5, Pages 708-718 doi: 10.1631/FITEE.1500402

Abstract: A generative model that combines hierarchical topic modeling and matrix factorization is proposed.Empirical results show that our model outperforms other state-of-the-art models, and can provide interpretabletopic structures for users and items.

Keywords： User-generated content (UGC) Collaborative filtering (CF) Matrix factorization (MF) Hierarchical topic

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Multi-domain Knowledge Convergence Trajectory Analysis of Strategic Emerging Industries Based on Citation Network and Text Information

Liu Yufei, Miao Zhongzhen, Li Lingfeng, Kong Dejing

Strategic Study of CAE 2020, Volume 22, Issue 2, Pages 120-129 doi: 10.15302/J-SSCAE-2020.02.016

Abstract: It utilizes a graph neural network model and encodes the citation network, title, and abstract of the

Keywords： emerging industries knowledge convergence graph neural networks citation network topic model

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Green Heating System——Topic of Critical Importance

Song Zhi-ping

Strategic Study of CAE 2001, Volume 3, Issue 6, Pages 9-14

Abstract:

Nowadays a topic of most concern is how to protect the global climate change and meet the increasing

Keywords： sustainable development water resource combined heat and power heat pump poly generation

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Topicmodeling for large-scale text data

Xi-ming LI,Ji-hong OUYANG

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 6, Pages 457-465 doi: 10.1631/FITEE.1400352

Abstract: This paper develops a novel online algorithm, namely moving average stochastic variational inference (MASVI), which applies the results obtained by previous iterations to smooth out noisy natural gradients. We analyze the convergence property of the proposed algorithm and conduct a set of experiments on two large-scale collections that contain millions of documents. Experimental results indicate that in contrast to algorithms named ‘stochastic variational inference’ and ‘SGRLD’, our algorithm achieves a faster convergence rate and better performance.

Keywords： Latent Dirichlet allocation (LDA) Topic modeling Online learning Moving average

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Seismic input of NPP & topic of seismic-isolated research for AP1000 nuclear island

Xia Zufeng

Strategic Study of CAE 2013, Volume 15, Issue 4, Pages 52-56

Abstract:

The article introduces seismic input of nuclear power plant in the world briefly, and mentions some exploratory work for seismic-isolated foundation of nuclear island in France, Japan and China. The article mainly focuses on a general concept design of nuclear island seismic-isolated foundation for AP1000 units by our institute. There are more useful information for seismic input of nuclear power plant & seismic-isolated foundation of nuclear island as a reference.

Keywords： nuclear power plant seismic design AP1000 seismic-isolated foundation

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Cohort-based personalized query auto-completion Regular Papers-Research Articles

Dan-yang JIANG, Hong-hui CHEN

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 9, Pages 1246-1258 doi: 10.1631/FITEE.1800010

Abstract: We build an individual’s interest profile by learning his/her topic preferences through topic modelsAs conventional topic models are unable to automatically learn cohorts, we propose two cohort topic modelsthat handle topic modeling and cohort discovery in the same framework.

Keywords： Query auto-completion Cohort-based retrieval Topic models

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Paper evolution graph: multi-view structural retrieval for academic literature None

Dan-ping LIAO, Yun-tao QIAN

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 2, Pages 187-205 doi: 10.1631/FITEE.1700105

Abstract: First, the papers are soft-clustered into communities via metagraph factorization, during which the topic

Keywords： Paper evolution graph Academic literature retrieval Metagraph factorization Topic coherence

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A Promising Topic in the Development of Electrical Engineering in the 21st Century ——Superconducting

Tang Yuejin,Li Jingdong,Duan Xianzhong,Cheng Shijie,Pan Yuan

Strategic Study of CAE 2000, Volume 2, Issue 4, Pages 1-7

Abstract:

In the new century, people will extensively concern themselves with environment protection and natural resource saving. Their life style will be changed rapidly. Information system will become the most important part of our society. All of these will put forward the following challenging requirements to the electric power system for high economic characteristics, high reliability, high quality, high quantity and high density of power supply. As the conventional technology used in current power system is difficult to meet these requirements, breakthroughs of revolution in electrical technology is in urgent need. Superconducting technology is one of those breakthroughs. It is commonly recognized that superconducting technology will be widely used in the electric power system in the 21st century. This paper systematically analyzes the problems facing the electrical power industry in the 21st century and the potential of using superconducting technology in the future power system. The current states of applying superconducting technology to the electric power system are also overviewed.

Keywords： applied superconductivity electric power system environment and resources

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Critical technique and scientific topic on fully polarized microwave radiometer remote sensing sea surface

Wang Zhenzhan,Jiang Jingshan,Liu Jingyi,Yin Xiaobin

Strategic Study of CAE 2008, Volume 10, Issue 6, Pages 76-86

Abstract: Oceanic emission and scattering model is develoked for remote sensing wind vector using passive polarimetricefforts are paid on expatiating scientific topics on wind reversion methods, including geophysical model

Keywords： polarimetric microwave radiometer wind vector retrieval calibration

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Standard model of knowledge representation

Wensheng YIN

Frontiers of Mechanical Engineering 2016, Volume 11, Issue 3, Pages 275-288 doi: 10.1007/s11465-016-0372-3

Abstract: methods include predicate logic, semantic network, computer programming language, database, mathematical modelintrinsic link between various knowledge representation methods, a unified knowledge representation modelAccording to ontology, system theory, and control theory, a standard model of knowledge representationThe model is composed of input, processing, and output.In addition, the standard model of knowledge representation provides a way to solve problems of non-precision

Keywords： knowledge representation standard model ontology system theory control theory multidimensional representation