2016 Eleventh International Conference on Digital Information Management (ICDIM)最新文献_第4页

SJSON: A succinct representation for JavaScript object notation documents json: JavaScript对象表示法文档的简洁表示

2016 Eleventh International Conference on Digital Information Management (ICDIM) Pub Date : 2016-09-01 DOI: 10.1109/ICDIM.2016.7829787

Edman Anjos, Junhee Lee, S. Rao

引用次数: 3

Information security and digital forensics in the world of cyber physical systems 网络物理系统世界中的信息安全和数字取证

2016 Eleventh International Conference on Digital Information Management (ICDIM) Pub Date : 2016-09-01 DOI: 10.1109/ICDIM.2016.7829795

Andrew Jones, S. Vidalis, N. Abouzakhar

引用次数: 7

Exploiting response patterns for identifying topical experts in StackOverflow 利用响应模式来识别StackOverflow中的专题专家

2016 Eleventh International Conference on Digital Information Management (ICDIM) Pub Date : 2016-09-01 DOI: 10.1109/ICDIM.2016.7829790

M. Bhanu, Joydeep Chandra

{"title":"Exploiting response patterns for identifying topical experts in StackOverflow","authors":"M. Bhanu, Joydeep Chandra","doi":"10.1109/ICDIM.2016.7829790","DOIUrl":"https://doi.org/10.1109/ICDIM.2016.7829790","url":null,"abstract":"The popularity of community question answer (CQA) forums like Stack Overflow, Yahoo Answers and Quora is increasing tremendously with thousands of questions being posted each day and about thrice the number of responses being provided. With such query explosion, users participating in these forums receive a huge number of postings that adversely affects their responsiveness and also the quality of the responses. Hence, identifying topical experts is necessary to improve the efficacy of these systems in terms of both response time and quality. Although expert detection in CQA forums has traditionally been a topic of wide interest, however, many of the proposed techniques use features set that reflect the popularity of the responses of the responder rather than the difficulty level of the questions being responded. In this paper we provide measures of labeling difficult questions and use the number of difficult questions responded by a user combined with other user interaction parameters in identifying potential topical experts. Using a random forest classifier with the proposed feature set on Stack Overflow data, we obtain an improvement in accuracy of 5–16% over existing techniques, in detecting topical experts.","PeriodicalId":146662,"journal":{"name":"2016 Eleventh International Conference on Digital Information Management (ICDIM)","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":"131421547","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}

引用次数: 5

Processing of multimedia aplications and their use in foreign language teaching 多媒体应用程序的处理及其在外语教学中的应用

2016 Eleventh International Conference on Digital Information Management (ICDIM) Pub Date : 2016-09-01 DOI: 10.1109/ICDIM.2016.7829793

S. Hubackova

引用次数: 0

Towards automatic generation of relevance judgments for a test collection 为测试集合自动生成相关判断

2016 Eleventh International Conference on Digital Information Management (ICDIM) Pub Date : 2016-09-01 DOI: 10.1109/ICDIM.2016.7829763

Mireille Makary, M. Oakes, Fadi Yamout

引用次数: 0

The evolution of C2C social commerce models C2C社交商务模式的演变

2016 Eleventh International Conference on Digital Information Management (ICDIM) Pub Date : 2016-09-01 DOI: 10.1109/ICDIM.2016.7829761

Supattana Sukrat, P. Mahatanankoon, B. Papasratorn

引用次数: 6

A data mining application on moving object data 移动对象数据的数据挖掘应用

2016 Eleventh International Conference on Digital Information Management (ICDIM) Pub Date : 2016-09-01 DOI: 10.1109/ICDIM.2016.7829757

Yasen Yakufu, C. Atay

引用次数: 3

A federation model to support semantic SPARQL queries for enterprise data governance 支持用于企业数据治理的语义SPARQL查询的联合模型

2016 Eleventh International Conference on Digital Information Management (ICDIM) Pub Date : 2016-09-01 DOI: 10.1109/ICDIM.2016.7829778

Antonio Corradi, L. Foschini, Alessandro Zanni, Mirco Casoni, S. Monti, Francesco Sprotetto

引用次数: 1

Grafeno: Semantic graph extraction and operation Grafeno:语义图的提取和操作

2016 Eleventh International Conference on Digital Information Management (ICDIM) Pub Date : 2016-09-01 DOI: 10.1109/ICDIM.2016.7829770

Antonio F. G. Sevilla, Alberto Fernández-Isabel, Alberto Díaz

引用次数: 1

A “Fast Data” architecture: Dashboard for anomalous traffic analysis in data networks “快速数据”架构:数据网络中异常流量分析的仪表板

2016 Eleventh International Conference on Digital Information Management (ICDIM) Pub Date : 2016-09-01 DOI: 10.1109/ICDIM.2016.7829756

Miguel Angel López Peña, C. Rua, Sergio Segovia Lozoya

{"title":"A “Fast Data” architecture: Dashboard for anomalous traffic analysis in data networks","authors":"Miguel Angel López Peña, C. Rua, Sergio Segovia Lozoya","doi":"10.1109/ICDIM.2016.7829756","DOIUrl":"https://doi.org/10.1109/ICDIM.2016.7829756","url":null,"abstract":"Fast Data is a new Big Data computing paradigm that ensures requirements such as Real-Time processing of continuous data stream, storage at high rates and low latency with no data losses. In this work we propose a “Fast Data” architecture for a specific kind of software application in which input data arrive very fast and the results for each processed data have to match such input rates. We applied this architecture to build a Dashboard for Anomalous Traffic Analysis in Data Networks. In order to fulfill the requirements of Real-Time processing and no data losses, we carry out a design that consists of a pattern of dynamic tree of process pipelines, where the number of branches increases proportionally to the input data rate. Two different approaches have been followed to implement this design pattern: one based in a well-known set of products from the Big Data ecosystem; and the other built with Kafka, Zookeeper and a set of components designed and implemented by us. These two implementations have been compared in terms of velocity and scalability performance. As a result, the implementation built with our own components is significantly faster and scalable than the traditional one. The good results obtained by using both the design pattern of dynamic tree of process pipelines and our implementation make them very suitable for its use in other scenarios and applications such as smart cities, environment monitoring, industry 4.0, distributed control systems, etc.","PeriodicalId":146662,"journal":{"name":"2016 Eleventh International Conference on Digital Information Management (ICDIM)","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":"130849725","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}

引用次数: 3