作者机构：
[Liu, Sannyuya; Zhao, Liang; Yan, Zhonghua] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.;[Liu, Sannyuya; Zhao, Liang; Yan, Zhonghua] Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan 430079, Hubei, Peoples R China.;[Cheng, Xiufeng] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Hubei, Peoples R China.
通讯机构：
[Yan, Zhonghua] C;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.;Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan 430079, Hubei, Peoples R China.
摘要：
To better capture typical individual response modes under strategic uncertainty in congestible networks, we conducted laboratory experiments in a network with two parallel routes under within-subject design. Sixty-four undergraduates were assigned into four sessions to make recurrent route-choice decisions under Condition partial-information (PI) first, and then under Condition full-information (FI). Individuals whose response modes are featured by a series of conditional probabilities regarding switching behaviour naturally cluster into three and four groups under Conditions PI and FI, respectively. An in-depth analysis of behavioural bases of each type was discussed. In Condition FI, the proportion of highly responsive players (holding Direct-response-like and Contrary-response-like patterns) and Highly-risk-averse players drops, whereas the Status-quo-maintenance category players stand out. More feedback information was disclosed for the purpose of reducing uncertainty but turned out to reduce the proportion of people who were highly responsive to the new information and who firmly commit themselves to a unique route.
作者机构：
[Ying, Zhiwei] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Hubei, Peoples R China.;[Huang, Jimmy Xiangji] York Univ, Sch Informat Technol, Informat Retrieval & Knowledge Management Res Lab, Toronto, ON M3J 1P3, Canada.;[Zhou, Jie] East China Normal Univ, Dept Comp Sci & Technol, Shanghai 200062, Peoples R China.;[Ying, Zhiwei] Cent China Normal Univ, Hubei Prov Key Lab Artificial Intelligence & Smar, Wuhan 430079, Hubei, Peoples R China.;[Ying, Zhiwei] Cent China Normal Univ, Natl Language Resources Monitor & Res Ctr Network, Wuhan 430079, Hubei, Peoples R China.
通讯机构：
[Huang, Jimmy Xiangji] Y;York Univ, Sch Informat Technol, Informat Retrieval & Knowledge Management Res Lab, Toronto, ON M3J 1P3, Canada.
关键词：
Digital signal processing;Probabilistic logic;Kernel;Information retrieval;Computational modeling;Time-domain analysis;Physics;Information retrieval;digital signal processing;kernels
摘要：
In recent decades, the vast majority of researchers in the field of information retrieval (IR) have been studying three main categories of IR models (i.e., vector space models, probabilistic models and statistical language models). Recently, some researchers have been exploring a new category of IR models which introduce the knowledge from the field of digital signal processing (DSP), which have been shown to be promising. However, the existing DSP-based models are not well-performed in some cases because they have not incorporated effective term weighting methods and the existing framework itself has some disadvantages to be overcome. In our research, we propose a new DSP-based IR model, denoted as DSP-MATF, which incorporates a very effective term weighing method from the well-performed Vector Space Model named Multi-Aspect Term Frequency (MATF). In addition, for improving the existing DSP-based IR frameworks, we consider each query term as a spectrum enveloped by different curves of seven kernel functions. To testify the effectiveness of our proposed model, we conduct extensive experiments on seven standard TREC datasets. The results show that in most cases our proposed model outperforms the strong baselines in terms of varied metrics.
期刊：
International Journal of Production Economics,2018年197(Mar.):52-62 ISSN：0925-5273
通讯作者：
Chen, Pengyu
作者机构：
[Xu, He; Lu, Fen] Huazhong Univ Sci & Technol, Sch Management, Wuhan, Hubei, Peoples R China.;[Chen, Pengyu] Cent China Normal Univ, Sch Informat Management, Wuhan, Hubei, Peoples R China.;[Zhu, Stuart X.] Univ Groningen, Fac Econ & Business, Dept Operat, Nettelbosje 2, NL-9747 AE Groningen, Netherlands.
通讯机构：
[Chen, Pengyu] C;Cent China Normal Univ, Sch Informat Management, Wuhan, Hubei, Peoples R China.
关键词：
Yield uncertainty;Downconversion;Pricing
摘要：
We consider a firm who supplies two types of products: high-end and low-end. Because of the uncertainty in the production process, the yield rate of the high-end products is uncertain. The substandard high-end products caused by the yield uncertainty can be transformed into the low-end products with a certain cost. We characterize the optimal pricing and production decisions and develop an algorithm to compute the optimal solution. We also investigate the impact of the yield uncertainty on the firm's performance, and explore how stability of market demand, emergent fulfillment costs, and downconversion cost influence this effect. We find that (i) the profit of the firm deteriorates when the risk of the yield uncertainty is high. In the face of yield uncertainty, the firm prefers to decrease (increase) the production quantity of the high-end (low-end) products; (ii) when the market demands are quite unstable, the emergent fulfillment costs are low, or the downconversion cost is high, the firm has a low incentive to eliminate the yield uncertainty.
摘要：
Third-party logistics (3PL) is a fast growing business. Many large organisations are using 3PL services to reduce operating costs, simplify business processes, and enhance operations and supply chain flexibility. In this paper, we study location-inventory decisions jointly in a closed-loop system with 3PL. First, a model formulation is proposed to develop mixed-integer non-linear programming (MINLP) models for the location-inventory problem under study. Then, a novel heuristics based on differential evolution and the genetic algorithm is designed to solve the MINLP models efficiently. Last, numerical study is presented to illustrate and validate the solution approach.
期刊：
ONLINE INFORMATION REVIEW,2018年42(3):304-323 ISSN：1468-4527
通讯作者：
Wang, Zefeng
作者机构：
[Li, Xuguang] Cent China Normal Univ, Dept Informat, Sch Management, Wuhan, Hubei, Peoples R China.;[Cox, Andrew] Univ Sheffield, Informat Sch, Sheffield, S Yorkshire, England.;[Wang, Zefeng] Shenzhen Energy Grp Co Ltd, Shenzhen, Peoples R China.
通讯机构：
[Wang, Zefeng] S;Shenzhen Energy Grp Co Ltd, Shenzhen, Peoples R China.
关键词：
Social capital;LinkedIn;Social network sites;Knowledge construction;Product users
期刊：
Journal of Coastal Research,2018年83(sp1):754-769 ISSN：0749-0208
通讯作者：
Zhong, Zufeng
作者机构：
[Duan, Yaoqing; Zhong, Zufeng; Yang, Shaofei] Cent China Normal Univ, Informat Management Dept, Wuhan 430079, Hubei, Peoples R China.;[Zhong, Zufeng] Lingnan Normal Univ, Sch Business, Zhanjiang 524048, Peoples R China.;[Zhong, Zufeng] Lingnan Normal Univ, South China Sea Silk Rd Collaborat Innovat Ctr, Zhanjiang 524048, Peoples R China.
通讯机构：
[Zhong, Zufeng] C;[Zhong, Zufeng] L;Cent China Normal Univ, Informat Management Dept, Wuhan 430079, Hubei, Peoples R China.;Lingnan Normal Univ, Sch Business, Zhanjiang 524048, Peoples R China.;Lingnan Normal Univ, South China Sea Silk Rd Collaborat Innovat Ctr, Zhanjiang 524048, Peoples R China.
摘要：
Sustainable development systems are a dynamic and complicated large systems, that can both be modestly destroyed and restrained by typhoon disasters. System dynamics can be used to study the problems of sustainable development. In this study, based on the theory of sustainable development and targeting typhoon disaster events in Leizhou Peninsula of China, we selected four subsystems (economy, population, environment, and water resource) using the background of typhoon disasters to empirically analyze the effectiveness and practicability of simulation models. Based on this, the restricting factors for sustainable development of the Leizhou Peninsula were assessed via scenario analysis. It was found that typhoon disasters introduced both benefits and harms to the economic development. The existing environmental protection investment did not meet the demands for social development, and the supply-demand contradiction of water resources remained severe. To promote sustainable development of the Leizhou Peninsula, the government has to adjust industrial structure, increase environmental investment, preserve water resources, and improve water quality.
作者机构：
[Zhang, Jun] Cent China Normal Univ, Informat Management Dept, Wuhan 430079, Hubei, Peoples R China.;[Wang, Xuping] Dalian Univ Technol, Inst Syst Engn, Dalian 116023, Peoples R China.;[Wang, Xuping] Dalian Univ Technol, Sch Business, Panjin 124221, Peoples R China.;[Huang, Kai] McMaster Univ, DeGroote Sch Business, Hamilton, ON L8S 4L8, Canada.
通讯机构：
[Zhang, Jun] C;Cent China Normal Univ, Informat Management Dept, Wuhan 430079, Hubei, Peoples R China.
关键词：
Integrated order picking and delivery;On-line scheduling;Competitive analysis;Multiple delivery zones;Vehicle capacity
摘要：
We consider the on-line business-to-customer (B2C) e-commerce supply chain scheduling problem where customers generate orders on-line that have to be picked from the shelves in a warehouse and delivered to the customers in different zones. The problem is identified as a specific integrated production-delivery problem, named on-line order picking and delivery problem with multiple delivery zones and limited vehicle capacity. The orders are grouped into batches and delivered to their assigned zones by the capacitated vehicles. The objective is to minimize the total cost, which is the sum of the makespan and the delivery cost. We present an on-line 4-competitive algorithm by integrating the existing methods for the on-line integrated production-delivery problem, the on-line batching machine problem, and the on-line order batching problem. Our extensive numerical experiments show that the proposed algorithm is robust and efficient. Moreover, through the comparison with the benchmark, it is demonstrated that the proposed model can lead to a substantial reduction of both the total cost and the delivery cost. (C) 2017 Elsevier Ltd. All rights reserved.
作者：
Ayala, Brenda Reyes*;Knudson, Ryan;Chen, Jiangping;Cao, Gaohui;Wang, Xinyue
期刊：
JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY,2018年69(1):47-59 ISSN：2330-1635
通讯作者：
Ayala, Brenda Reyes
作者机构：
[Knudson, Ryan; Chen, Jiangping; Ayala, Brenda Reyes] Univ North Texas, Dept Informat Sci, 1155 Union Circle 311068, Denton, TX 76203 USA.;[Cao, Gaohui] Cent China Normal Univ, Sch Informat Management, 152 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China.;[Wang, Xinyue] Univ North Texas, Intelligent Informat Access Lab, 1155 Union Circle 311068, Denton, TX 76203 USA.
通讯机构：
[Ayala, Brenda Reyes] U;Univ North Texas, Dept Informat Sci, 1155 Union Circle 311068, Denton, TX 76203 USA.
摘要：
One way to facilitate Multilingual Information Access (MLIA) for digital libraries is to generate multilingual metadata records by applying Machine Translation (MT) techniques. Current online MT services are available and affordable, but are not always effective for creating multilingual metadata records. In this study, we implemented 3 different MT strategies and evaluated their performance when translating English metadata records to Chinese and Spanish. These strategies included combining MT results from 3 online MT systems (Google, Bing, and Yahoo!) with and without additional linguistic resources, such as manually-generated parallel corpora, and metadata records in the two target languages obtained from international partners. The open-source statistical MT platform Moses was applied to design and implement the three translation strategies. Human evaluation of the MT results using adequacy and fluency demonstrated that two of the strategies produced higher quality translations than individual online MT systems for both languages. Especially, adding small, manually-generated parallel corpora of metadata records significantly improved translation performance. Our study suggested an effective and efficient MT approach for providing multilingual services for digital collections.
摘要：
Many datasets that exists in the real world are often comprised of different representations or views which provide complementary information to each other. To integrate information from multiple views, data integration approaches such as nonnegative matrix factorization (NMF) have been developed to combine multiple heterogeneous data simultaneously to obtain a comprehensive representation. In this paper, we proposed a novel variant of symmetric nonnegative matrix factorization (SNMF), called Laplacian regularization based joint symmetric nonnegative matrix factorization (LJ-SNMF) for clustering multi-view data. We conduct extensive experiments on several realistic datasets including Human Microbiome Project data. The experimental results show that the proposed method outperforms other variants of NMF, which suggests the potential application of LJ-SNMF in clustering multi-view datasets. Additionally, we also demonstrate the capability of LJ-SNMF in community finding.
摘要：
It is very significant for us to predict future energy consumption accurately. As for China’s energy consumption annual time series, the sample size is relatively small. This paper combines the traditional auto-regressive model with group method of data handling (GMDH) suitable for small sample prediction, and proposes a novel GMDH based auto-regressive (GAR) model. This model can finish the modeling process in self-organized manner, including finding the optimal complexity model, determining the optimal auto-regressive order and estimating model parameters. Further, four different external criteria are proposed and the corresponding four GAR models are constructed. The authors conduct empirical analysis on three energy consumption time series, including the total energy consumption, the total petroleum consumption and the total gas consumption. The results show that AS-GAR model has the best forecasting performance among the four GAR models, and it outperforms ARIMA model, BP neural network model, support vector regression model and GM (1, 1) model. Finally, the authors give the out of sample prediction of China’s energy consumption from 2014 to 2020 by AS-GAR model.
