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Tseng F.S.C.,National Kaohsiung First University of Science and Technology | Kuo Y.-H.,Innovative DigiTech Enabled Applications and Services Institute | Huang Y.-M.,National Cheng Kung University
Information Sciences | Year: 2010

Existing parallel algorithms for association rule mining have a large inter-site communication cost or require a large amount of space to maintain the local support counts of a large number of candidate sets. This study proposes a de-clustering approach for distributed architectures, which eliminates the inter-site communication cost, for most of the influential association rule mining algorithms. To de-cluster the database into similar partitions, an efficient algorithm is developed to approximate the shortest spanning path (SSP) to link transaction data together. The SSP obtained is then used to evenly de-cluster the transaction data into subgroups. The proposed approach guarantees that all subgroups are similar to each other and to the original group. Experiment results show that data size and the number of items are the only two factors that determine the performance of de-clustering. Additionally, based on the approach, most of the influential association rule mining algorithms can be implemented in a distributed architecture to obtain a drastic increase in speed without losing any frequent itemsets. Furthermore, the data distribution in each de-clustered participant is almost the same as that of a single site, which implies that the proposed approach can be regarded as a sampling method for distributed association rule mining. Finally, the experiment results prove that the original inadequate mining results can be improved to an almost perfect level. © 2010 Elsevier B.V. All rights reserved. Source


Peng Y.-H.,Innovative DigiTech Enabled Applications and Services Institute | Yang C.-B.,National Sun Yat - sen University
Information and Computation | Year: 2014

The longest common subsequence (LCS) problem with gap constraints (or the gapped LCS), which has applications to genetics and molecular biology, is an interesting and useful variant to the LCS problem. In previous work, this problem is solved in O(nm) time when the gap constraints are fixed to a single integer, where n and m denote the lengths of the two input sequences A and B, respectively. In this paper, we first generalize the problem from fixed gaps to variable gap constraints. Then, we devise an optimal approach for the incremental suffix maximum query (ISMQ), which helps us obtain an efficient algorithm with O(nm) time for finding LCS with variable gap constraints. In addition, our technique for ISMQ can be applied to solve one of the block edit problems on strings, reducing the time complexity from O(nmlogm+m2) to O(nm+m2). Hence, the result of this paper is beneficial to related research on sequence analysis and stringology. © 2014 Elsevier Ltd. All rights reserved. Source


Chen H.-H.,National Sun Yat - sen University | Yang C.-B.,National Sun Yat - sen University | Peng Y.-H.,Innovative DigiTech Enabled Applications and Services Institute
Applied Soft Computing Journal | Year: 2014

The aim of this paper is to combine several techniques together to provide one systematic method for guiding the investment in mutual funds. Many researches focus on the prediction of a single asset time series, or focus on portfolio management to diversify the investment risk, but they do not generate explicit trading rules. Only a few researches combine these two concepts together, but they adjust trading rules manually. Our method combines the techniques for generating observable and profitable trading rules, managing portfolio and allocating capital. First, the buying timing and selling timing are decided by the trading rules generated by gene expression programming. The trading rules are suitable for the constantly changing market. Second, the funds with higher Sortino ratios are selected into the portfolio. Third, there are two models for capital allocation, one allocates the capital equally (EQ) and the other allocates the capital with the mean variance (MV) model. Also, we perform superior predictive ability test to ensure that our method can earn positive returns without data snooping. To evaluate the return performance of our method, we simulate the investment on mutual funds from January 1999 to September 2012. The training duration is from 1999/1/1 to 2003/12/31, while the testing duration is from 2004/1/1 to 2012/9/11. The best annualized return of our method with EQ and MV capital allocation models are 12.08% and 12.85%, respectively. The latter also lowers the investment risk. To compare with the method proposed by Tsai et al., we also perform testing from January 2004 to December 2008. The experimental results show that our method can earn annualized return 9.07% and 11.27%, which are better than the annualized return 6.89% of Tsai et al. © 2013 Elsevier B.V. All rights reserved. Source


Li H.-C.,National Taiwan University | Liang P.-H.,National Chengchi University | Yang J.-M.,National Chengchi University | Chen S.-J.,Innovative DigiTech Enabled Applications and Services Institute
Proceedings - IEEE International Conference on E-Business Engineering, ICEBE 2010 | Year: 2010

Cloud computing delivery model can significantly reduce enterprise IT costs and complexities. This technology can handle the rapidly gowning environment and provide more flexible resources sharing and hence it has become as a new information technology infrastructure recently. In contrast to traditional enterprise IT solution, cloud computing moves the application software and databases to the servers in large datacenters which raise many security challenges. The business model now allows the users to purchase the capacity they require when they require it. The providers can maximize the utilization by multiplexing customer virtual machines (VMs) across a shared physical infrastructure. In the shared cloud environment, it would be possible to launch an attack cross VMs. How to define the policies for individual virtual firewall becomes more important. In this paper, we investigate the different security vulnerability assessments among the cloud environments. Experiment shows there are more vulnerability happened if vulnerability tools and the servers are in the same LAN. In other word, the hackers can find an easier way to get the target information if sit on the same LAN. This experimental result can be used to analysis the risk in third party compute clouds. © 2010 IEEE. Source


Lee C.-H.,National Taipei University of Technology | Lee C.-H.,Innovative DigiTech Enabled Applications and Services Institute | Wang Y.-H.,National Taipei University of Technology | Trappey A.J.C.,National Tsing Hua University
Advanced Engineering Informatics | Year: 2015

This study refines a structural service design stages based on the Theory of Inventive Problem Solving (TRIZ) and the service blueprint approach. This study uses the case study of intelligent parking services with the mobile application technology and vehicle license plate recognition system in a high-end shopping mall. In the problem definition stage, the research analyzes the enterprise problem. In the service resolution stage, the TRIZ contradiction analysis and the service blueprint of the parking service as it existed is depicted from the principles of problem resolution. In the solution evaluation stage, new intelligent parking mobile applications (apps) are proposed following the principles generated in the second stage. Furthermore, the failure points and waiting points in the prior service blueprint are overcome and the new service performance is significantly improved. It contributes to enriching the service design literature, and extends the range of TRIZ applications for future parking technology. © 2014 Elsevier Ltd. Source

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