{"title":"Parallel singular value decomposition on heterogeneous multi-core and multi-GPU platforms","authors":"Xiaowen Feng, Hai Jin, Ran Zheng, Lei Zhu","doi":"10.1109/ICDIM.2014.6991397","DOIUrl":"https://doi.org/10.1109/ICDIM.2014.6991397","url":null,"abstract":"Singular value decomposition (SVD) is one of the most fundamental matrix calculations in numerical linear algebra. Traditional solution is the QR-iteration-based SVD algorithm on CPU, and it is time-consuming. Nowadays, Graphics Processing Units (GPUs) are suited for many general purpose tasks and have emerged as low price and high performance accelerators. In this paper, the parallel-friendly divide-and-conquer approach is employed to accelerate SVD algorithm on the heterogeneous multicore and multi-GPU systems. Two mechanisms are designed to make good use of the computational resource on the heterogeneous system, including two-layer divide-and-conquer and coordination between CPU and GPU. The experimental results show that our algorithm is faster than Intel MKL with four CPU cores, and reaches 45 times speedup with four NVIDIA GTX460 GPUs over LAPACK. Our implementation can also achieve about 1.5 times speedup by doubling the number of GPU devices.","PeriodicalId":407225,"journal":{"name":"Ninth International Conference on Digital Information Management (ICDIM 2014)","volume":"2000 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128230076","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 elements-based multi-stage charges identification model for textual criminal cases","authors":"S. Thammaboosadee","doi":"10.1109/ICDIM.2014.6991415","DOIUrl":"https://doi.org/10.1109/ICDIM.2014.6991415","url":null,"abstract":"This paper proposes an identifying methodology of the relevant criminal offences charges, given textual information of the criminal cases in the Civil Law system. The model is devised as a multi-stage based on the criminal law codes. The first stage is to identify action types, using modular classifier. The modularity is designed based on the offences charges, which were abstractly categorized by elements of crimes in criminal codes. The second stage is to identify the legal elements, leading to general provisions. This classification stage is designed as independent multi-classifiers. The input data is preprocessed from text to features by some natural language processing methods. The integrated model aims at achieving high accuracy of classification while reserving explainable results, which is required in an application of legal domain.","PeriodicalId":407225,"journal":{"name":"Ninth International Conference on Digital Information Management (ICDIM 2014)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114659376","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}
Giovanni Yoko Kristianto, Goran Topic, Akiko Aizawa
{"title":"Exploiting textual descriptions and dependency graph for searching mathematical expressions in scientific papers","authors":"Giovanni Yoko Kristianto, Goran Topic, Akiko Aizawa","doi":"10.1109/ICDIM.2014.6991403","DOIUrl":"https://doi.org/10.1109/ICDIM.2014.6991403","url":null,"abstract":"Mathematical expressions are important for communication of scientific information, for instance, to explain or define concepts written in natural language. Despite their importance, current conventional search systems can not establish access to the mathematical expressions contained in a scientific paper. The major focus of current development of mathematical search systems is mathematical tree structure indexing, but utilizing textual information surrounding the expressions in these systems is also important. We examine how textual information contributes to a mathematical search system, primarily in the ranking process. We investigate the impact of two types of textual information in the ranking performances of a mathematical search system: words in context windows (baseline), which is easily extracted from sentence tokenization result, and descriptions, which are extracted using a machine learning method. We also examine the improvement in ranking obtained by utilizing the dependency graph of mathematical expressions. The experiment results show that the use of description and dependency graph together deliver better ranking performance than the use of context or when no textual information is used. The results also show that the dependency graph is crucial for increasing the number of mathematical expressions being assigned descriptions, and thus its use with descriptions together presented higher ranking performance than the use of descriptions only. This study suggests that descriptions represent mathematical expressions better (more precisely) than context windows, and even descriptions from child (indirect) expressions still represent the target expression better than the context from the target expression itself.","PeriodicalId":407225,"journal":{"name":"Ninth International Conference on Digital Information Management (ICDIM 2014)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123002161","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":"How rational are people? Economic behavior based on sentiment analysis","authors":"Nora Al Mohanna, Hend Suliman Al-Khalifa","doi":"10.1109/ICDIM.2014.6991405","DOIUrl":"https://doi.org/10.1109/ICDIM.2014.6991405","url":null,"abstract":"User-generated content plays a major role on the Web. It allows community websites to prosper as people seek each other's opinions before making their own choice. In this paper, we propose a novel approach to investigate the correlation between the sentiments' scores extracted from review text and the number of likes/dislikes for restaurants reviews, we also explore how the sentiments' scores affect the rating of restaurants. We formalize our problem under the rational choice theory, in which a person would make a choice among set of alternatives that have different utility that is calculated based on some measures. We propose to use different combination of measures including the number of likes/dislikes, and different sentiments scores that are generated manually and automatically. Results show how top ten restaurants fluctuated when different utility measures were used. Based on our initial results, we encourage future research in applying economics' theories on user-generated content to help in the process of sentiment analysis and decision making.","PeriodicalId":407225,"journal":{"name":"Ninth International Conference on Digital Information Management (ICDIM 2014)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114923267","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 reverse far neighbors search","authors":"Atsuhiro Ichikawa, Hanxiong Chen, K. Furuse","doi":"10.1109/ICDIM.2014.6991411","DOIUrl":"https://doi.org/10.1109/ICDIM.2014.6991411","url":null,"abstract":"Among the variations of similarity search in data engineering, Reverse Farthest Neighbors(RFN) query is one of the newest and is attracting more attention. RFN is likely to find its applications in facility location problem, product evaluation, social network system, and so on. Given an object set O and a query object q, the RFN query retrieves the objects of O, which take q as their farthest neighbor. The result of an RFN is affected significantly by outliers because it compares only the farthest neighbor. In this paper, we propose a general Reverse Far Neighbors Search and develop an efficient algorithm. Experiments on synthetic and real data confirmed the efficiency.","PeriodicalId":407225,"journal":{"name":"Ninth International Conference on Digital Information Management (ICDIM 2014)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115186423","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":"Automated DD-path testing: A challenging task in software testing","authors":"H. Sattar, Imran Sarwar Bajwa, U. Shafi, I. Haq","doi":"10.1109/ICDIM.2014.6991432","DOIUrl":"https://doi.org/10.1109/ICDIM.2014.6991432","url":null,"abstract":"Testing process ensures proper working of software. However, major hurdles during this process occur due to manual handling of a lot of overhead of software testing. Since software testing process is majorly categorized into functional and structural testing, each of them focuses on different aspect of software. Both structural and functional testing faces a lot of challenges during manual conduction. Focus of this research paper is to find out challenges of structural testing methodology “DD path testing” in manual environment and suggest suitable solution to face such challenges. Suggested solution describes a number of steps involve in DD path testing and the way the particular steps can be automated.","PeriodicalId":407225,"journal":{"name":"Ninth International Conference on Digital Information Management (ICDIM 2014)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114846107","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}
D. Al-Dabass, V. Colla, Marco Vannuci, A. Pantelous
{"title":"Welcome message from the chairs","authors":"D. Al-Dabass, V. Colla, Marco Vannuci, A. Pantelous","doi":"10.1109/EMS.2016.006","DOIUrl":"https://doi.org/10.1109/EMS.2016.006","url":null,"abstract":"Nowadays, providing personalized service to customers is one of the main issues in big data services. To provide the personalized service, analyzing various logs and cooperation between data analysts and developers are critical. However, the problem is that overhead can occur when the log data is analyzed due to general characteristics of big data system as well-known 4Vs(Velocity, Various, Value and Volume). Also, generally it is hard for data analysts and developers to work together because they use different interfaces. Therefore, we propose a personalized log analysis system including rule-based data grouping method in order for the improved performance of personalized log analysis and more flexible cooperation between data analysts and developers. The evaluation of the proposed system performs well for cooperation and grouping along with the R SW tool.","PeriodicalId":407225,"journal":{"name":"Ninth International Conference on Digital Information Management (ICDIM 2014)","volume":"54 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115977443","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}