{"title":"DQFIRD: Towards Data Quality-Based Filtering and Ranking of Datasets for Data Portals","authors":"Wenze Xia, Zhuoming Xu, Jie Wei, Haimei Tian","doi":"10.1109/WISA.2016.14","DOIUrl":"https://doi.org/10.1109/WISA.2016.14","url":null,"abstract":"The Data on the Web Best Practices Working Group, as part of W3C Data Activity, is standardizing the Data Quality Vocabulary (DQV) for expressing data quality of datasets published on the Web. By exploiting such DQV-based quality metadata associated to the datasets in a data portal, data consumers can achieve data quality-based filtering and ranking of datasets on the portal's conventional search results to obtain desired datasets with high data-quality. Despite the significant progress in standardization, there is a lack of systematic research on approaches and tools for data quality-based filtering and ranking of Web published datasets. This paper therefore proposes a generic software framework for Data Quality-based Filtering and Ranking of Datasets (DQFIRD) in data portals. DQFIRD adopts faceted search (or faceted exploration) techniques to filter the search results of a data portal based on quality metadata about the resulting datasets, and then ranks the filtered datasets according to numeric values of quality measurements in the metadata. We designed the main algorithms of DQFIRD and implemented a prototype of DQFIRD using Java and Jena API. Furthermore, we used the prototype to conduct case study experiments and time efficiency test on the Faceted Taxonomy Materialization (FTM) algorithm, the most time-consuming online operation algorithm in DQFIRD. The results indicate that the proposed DQFIRD approach is implementable and effective, and it has low time complexity because the run-time of the FTM algorithm exhibits approximately a linear growth rate as the size of the relevant dataset quality metadata increases.","PeriodicalId":308797,"journal":{"name":"2016 13th Web Information Systems and Applications Conference (WISA)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129893311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Space Disturbing Based Uncertainty Trajectory Anonymous Algorithm in Trajectory Databases Publication","authors":"Fengyun Li, Peng Li, Jinhua Yang","doi":"10.1109/WISA.2016.49","DOIUrl":"https://doi.org/10.1109/WISA.2016.49","url":null,"abstract":"In recent years, privacy preserving trajectory data publishing has gained widespread attention. Aiming at the trajectory anonymity issues in publishing trajectory data of moving target, using the inherent uncertainty of the trajectory acquisition system, and based on the case that the uncertain threshold of trajectory is variable in practical applications, the traditional (k, δ)-anonymous model was improved, and a (k, ∆)-anonymous model is proposed. Based on the (k, ∆)-anonymous model, a space disturbing based trajectory anonymous algorithm is proposed. Simulation results show that the proposed algorithm has better performance in terms of data quality and data availability.","PeriodicalId":308797,"journal":{"name":"2016 13th Web Information Systems and Applications Conference (WISA)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123279152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Enhancing Data Secrecy with Segmentation Based Isolation","authors":"Chi Zhang, Hui He, Xiaoguang Wang, Yichen Li, Xin Gao, Yong Qi","doi":"10.1109/WISA.2016.48","DOIUrl":"https://doi.org/10.1109/WISA.2016.48","url":null,"abstract":"Software memory disclosure attacks, such as buffer over-read, often work quietly and may cause leakage of secrets. The well-known OpenSSL Heartbleed vulnerability leaked out millions of servers' private keys, and caused most of Internet services insecure during that time. Existing solutions are either hard to apply to large code bases, or too heavyweight (e.g. by involving a hypervisor software or a modified operating system kernel). We propose SecSeg, an easy-to-use and lightweight system which leverages the traditional x86 segmentation mechanism to isolate the secrets from the remaining data. Software developers can prevent the secrets from being leaked out by simply declaring the secret variables with secure keyword. And our customized compiler will automatically separate the secrets from the remaining ones with an isolated hardware segment. Any legal instructions that have to visit the secrets will be automatically instrumented to special machine instructions which have access to the isolated segment. We have implemented an early SecSeg prototype with an open source compiler framework - the LLVM Compiler Infrastructure. The prototype proves that SecSeg is both secure and efficient.","PeriodicalId":308797,"journal":{"name":"2016 13th Web Information Systems and Applications Conference (WISA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129433222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Educational Resource Retrieval Mechanism Based on Lucene and Topic Index","authors":"Xiaomei Chen, Lizhen Xu","doi":"10.1109/WISA.2016.34","DOIUrl":"https://doi.org/10.1109/WISA.2016.34","url":null,"abstract":"In order to improve the retrieval performance in the educational resource database, this paper designs an retrieval mechanism called ERRM based on Lucene and topic index. Firstly, this paper introduces the full-text search engine – Lucene, and studies in depth its internal implementation. Then by the way of the topic index which is learned by the topic model, this paper researches how to successfully expand query semantics. Based on Lucene and topic index, this paper proposes a new retrieval mechanism for educational resources. After expanding the user query, the retrieval mechanism submits the enriched query condition to Lucene for full-text retrieval. The experimental results show that the proposed mechanism could obviously improve the retrieval performance and precision.","PeriodicalId":308797,"journal":{"name":"2016 13th Web Information Systems and Applications Conference (WISA)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121049426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Recommendation System Algorithm Based on Large Scale Internet Environment","authors":"Xifeng Liu, Zhijian Wang, Feng Ye","doi":"10.1109/WISA.2016.31","DOIUrl":"https://doi.org/10.1109/WISA.2016.31","url":null,"abstract":"With the growing scale of the Internet, the amount of data is increasing rapidly as well. In order to improve the user experience, the recommendation system came into being. It recommends products to the user by analyzing the user's behavior. In the recommendation system, collaborative filtering algorithm is one of the most widely used algorithms. While the traditional collaborative filtering is no longer suitable for large-scale network, where the algorithm efficiency is low, as well as, it has the extremely sparse problem. To solve those problems, we designed an improved collaborative filtering algorithm for network segmentation. The algorithm uses a segmentation rules to partition the large-scale network, and decompose the problem into sub-problems. Ultimately, it can help us to meet the purpose of optimizing the algorithm.","PeriodicalId":308797,"journal":{"name":"2016 13th Web Information Systems and Applications Conference (WISA)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126057645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Implementation of Database Partitioning Based on Streaming Framework","authors":"M. Guo, Hong Kang","doi":"10.1109/WISA.2016.40","DOIUrl":"https://doi.org/10.1109/WISA.2016.40","url":null,"abstract":"Horizontal and vertical partitioning can increase the performance of the database and simplify data management. However traditional partitioning techniques can't deal with stream queries efficiently. In this paper we present WSPS: a workload-driven stream partitioning system to solve the above problembytheintegrationofpartitioningtechnologyandstreaming framework. We construct a dynamic data model, cluster and merge nodes according to the node affinity, then get the optimal partitioning scheme according to a cost model. WSPS can deal with stream data and obtain real time partitioning scheme. Experimental results show that WSPS can improve the partitioning efficiency and reduce the computing complexity. Additionally, WSPS has good performance on horizontal scaling and high-throughput adaption.","PeriodicalId":308797,"journal":{"name":"2016 13th Web Information Systems and Applications Conference (WISA)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125086646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Efficient Subgraph Matching in Large Graph with Partitioning Scheme","authors":"Xiaofang Xie, Zhongwei Li, Haiwei Zhang","doi":"10.1109/WISA.2016.16","DOIUrl":"https://doi.org/10.1109/WISA.2016.16","url":null,"abstract":"Recently, subgraph matching has been implemented in more and more domains, such as social network and semantic web. An approximated solution for subgraph matching named strong simulation has been put forward. Strong Simulation can preserve the topology of data graphs and find a bounded number of matches, but the complexity further holds a cubic-time, so it's yet intractable to deal with large graphs. To solve the problem, this paper focuses on a partition scheme to reduce the search space of subgraph matching algorithm. Firstly, we present a pruning method on data graph based on the connection relationships of nodes and edges in query graph. Secondly, we propose to use a multilevel partitioning algorithm when the subgraphs we get from former step are too large. Thirdly, we propose an algorithm for subgraph matching based on the partitioning scheme, which can preserve the topology of query graph and guarantee the correctness of results. Lastly, we experimentally prove the effectiveness and efficiency of this scheme, both using real-life data and synthetic data. It turns out that our method is quite efficient and the matching results are also satisfactory.","PeriodicalId":308797,"journal":{"name":"2016 13th Web Information Systems and Applications Conference (WISA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128838526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Improved Flower Pollination Algorithm","authors":"Mingxin Zhang, Jiao Dai, Jinlong Zheng, Guohai Zhang","doi":"10.1109/WISA.2016.44","DOIUrl":"https://doi.org/10.1109/WISA.2016.44","url":null,"abstract":"In order to solve the problems of the poor local deeply searching ability, easily falling into local optimum, and the low convergence rate in the late iteration of the Flower Pollination Algorithm (FPA), a Flower Pollination Algorithm based on Adaptive Gauss Mutation and Shuffled Frog Leaping (AGM-SFLFPA) is proposed. First, drawing on the thoughts of Shuffled Frog Leaping Algorithm (SFLA), AGM-SFLFPA sorts the population according to the fitness value of individual, groups them and updates the location of the worst individual in each group. It not only enhances the local depth search ability, but also increases the population diversity. Then, Gauss mutation strategy is introduced, which is automatically performed on the global optimal individuals when the algorithm falls into the local optimal solution. The proposed algorithm not only improves the ability of the individual to jump out of the local optimum, but also increases the diversity of the population and accelerates the convergence rate. In this paper, four standard test functions are used to verify the validity of AGM-SFLFPA from four aspects. The experimental results show that AGM-SFLFPA has better stability and reliability, faster convergence speed and higher precision, which is suitable for solving high dimensional multi-extremum complex function problems.","PeriodicalId":308797,"journal":{"name":"2016 13th Web Information Systems and Applications Conference (WISA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121535294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Augmented Reality in IT Operation Management of Power System","authors":"Li Li, Xingzhi Wang, Yao Xu","doi":"10.1109/WISA.2016.13","DOIUrl":"https://doi.org/10.1109/WISA.2016.13","url":null,"abstract":"Augmented reality (AR) is an environment-enhancing technology, which has recently widely applied in various fields. The present study aims to provide an alternative approach to use augmented reality to assist the Information Technology (IT) operation and maintenance management in the power system. This paper presents the characteristics of IT operation management in power grid and the visual requirements, then the potentials of AR applications in IT management are discussed. The design and architecture of the IT operation management system of power grid with AR are also provided in this paper. An application with the technology of augmented reality has developed to demonstrate the analysis report on IT management in power grid, specifically on the reports of engine room, IT equipment, application systems and security. Such application helps operators and managers improve the way of analyzing the IT environment by visualizing the 3D world, assets, monitoring, and demonstration, which enables the users to understand the analysis reports more interactively, intuitively and efficiently. Finally this paper provides some other future research directions, and the conclusion that AR will play a key role and make significant contribution in improving the operation of the power system.","PeriodicalId":308797,"journal":{"name":"2016 13th Web Information Systems and Applications Conference (WISA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115063279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Recommendation Based on Bipartite Network of Two-Step Model","authors":"Liting Wei, Yun Li","doi":"10.1109/WISA.2016.21","DOIUrl":"https://doi.org/10.1109/WISA.2016.21","url":null,"abstract":"Traditional recommendation only uses the single model of selection or rating to mining the users' interests. Network-Based Inference (NBI) is typical of selection single model. In order to make full use of information, in this paper, Recommendation based on bipartite network of two-step model(RBNTM) is put forward. The method on the basis of Network-based inference, considering scores also reflects the degree of the user preferences, combining NBI and rating prediction with two-step model to improve the accuracy of the prediction. On MoiveLens datasets experiments show that the proposed, RBNTM is effective.","PeriodicalId":308797,"journal":{"name":"2016 13th Web Information Systems and Applications Conference (WISA)","volume":"15 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121890969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}