Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business最新文献_第4页

Science with and without e 有和没有e的科学

Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business Pub Date : 2015-10-21 DOI: 10.1145/2809563.2809619

Claudia Koschtial, Carsten Felden, Stefan Lardong

引用次数: 0

MicroTrails MicroTrails

Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business Pub Date : 2015-10-21 DOI: 10.1145/2809563.2809608

Martin Becker, Kathrin Borchert, Matthias Hirth, Hauke Mewes, A. Hotho, P. Tran-Gia

{"title":"MicroTrails","authors":"Martin Becker, Kathrin Borchert, Matthias Hirth, Hauke Mewes, A. Hotho, P. Tran-Gia","doi":"10.1145/2809563.2809608","DOIUrl":"https://doi.org/10.1145/2809563.2809608","url":null,"abstract":"To optimize the workflow on commercial crowdsourcing platforms like Amazon Mechanical Turk or Microworkers, it is important to understand how users choose their tasks. Current work usually explores the underlying processes by employing user studies based on surveys with a limited set of participants. In contrast, we formulate hypotheses based on the different findings in these studies and, instead of verifying them based on user feedback, we compare them directly on data from a commercial crowdsourcing platform. For evaluation, we use a Bayesian approach called HypTrails which allows us to give a relative ranking of the corresponding hypotheses. The hypotheses considered, are for example based on task categories, monetary incentives or semantic similarity of task descriptions. We find that, in our scenario, hypotheses based on employers as well the the task descriptions work best. Overall, we objectively compare different factors influencing users when choosing their tasks. Our approach enables crowdsourcing companies to better understand their users in order to optimize their platforms, e.g., by incorparting the gained knowledge about these factors into task recommentation systems.","PeriodicalId":20526,"journal":{"name":"Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business","volume":"48 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74155526","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

Enacting skilful performance in organizations: (the practice of turning theory into practice) 在组织中表演技巧:(将理论转化为实践的实践)

Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business Pub Date : 2015-10-21 DOI: 10.1145/2809563.2809565

Eva Gatarik, R. Born, Viktor Kulhavý

{"title":"Enacting skilful performance in organizations: (the practice of turning theory into practice)","authors":"Eva Gatarik, R. Born, Viktor Kulhavý","doi":"10.1145/2809563.2809565","DOIUrl":"https://doi.org/10.1145/2809563.2809565","url":null,"abstract":"Pointing out flaws and errors can be a risky pastime for employees, when the information therein conflicts with rules, practices and theories held dear by management. However, skilful performance is not about strictly adhering to established practice when seeking ways out of problem situations. Instead, it is shown that skilful performance arises out of shared meaning rather than accuracy. Particularly in the event of uncertainty, equivocation and doubt, people in organizations should not just follow given rules, practices and theories, but jointly classify, interpret and transform observed data into new knowledge that feeds back, so that subsequent action and its justification can tap into the prevailing business climate, reduce ambiguity, and offer more exciting prospects. A systemic approach is applied to generalize the construction, processing and justification of knowledge to establish meaning within an organization in order to sustainably improve its performance. Finally, the presuppositions for an appropriate actualization of this approach within an organization are discussed.","PeriodicalId":20526,"journal":{"name":"Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business","volume":"116 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74836617","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: 1

Using machine learning for unsupervised maritime waypoint discovery from streaming AIS data 从流式AIS数据中使用机器学习进行无监督海上航路点发现

Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business Pub Date : 2015-10-21 DOI: 10.1145/2809563.2809573

Andrej Dobrkovic, M. Iacob, J. Hillegersberg

{"title":"Using machine learning for unsupervised maritime waypoint discovery from streaming AIS data","authors":"Andrej Dobrkovic, M. Iacob, J. Hillegersberg","doi":"10.1145/2809563.2809573","DOIUrl":"https://doi.org/10.1145/2809563.2809573","url":null,"abstract":"Estimating the future position of a deep sea vessel more than 24 hours in advance is a major challenge for Dutch logistics service providers (LSPs). Their unscheduled arrival in ports directly impacts scheduling and waiting times of barges, propagating throughout the entire supply chain network. To help LSPs' planners improve planning operations, we intend to capture the characteristics of maritime routes for a specific region (the North Sea connecting the Netherlands and United Kingdom) in the form of a directed graph, which can be used as a foundation for predicting destination and arrival time of each associated vessel. To create such graph we need an efficient way to extract waypoints for traffic data and this is the problem we will address in this paper. Since LSPs only use publicly available data for arrival estimation, our solution is entirely based on Automatic Identification System (AIS) data. Extracting positional information from AIS, we explore various machine learning approaches to identify clusters. We apply DBSCAN algorithm and show its advantages and disadvantages when used on AIS data. The same process is repeated using meta-heuristics, comparing clustering results generated by a genetic algorithm and by modified ant-colony optimization to those produced by DBSCAN. Finally, we present a hybrid approach and its ability to discover waypoints, highlighting the achieved improvements. To extend the problem, two constraints are added. The first is the requirement to handle large volumes of streaming AIS data on standard PC-based hardware. The second introduces the common situation of \"dark areas\" in a map due to problems with receiving and transmitting AIS data. The algorithm discovers route waypoints in efficient and effective ways under these constraints.","PeriodicalId":20526,"journal":{"name":"Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business","volume":"71 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80535404","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: 33

WebOCD: a RESTful web-based overlapping community detection framework WebOCD:基于rest的基于web的重叠社区检测框架

Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business Pub Date : 2015-10-21 DOI: 10.1145/2809563.2809593

Mohsen Shahriari, Sebastian Krott, R. Klamma

引用次数: 5

Building an open data visualisation web app using a data server: the Styrian diversity visualisation project 使用数据服务器构建一个开放的数据可视化web应用:Styrian多样性可视化项目

Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business Pub Date : 2015-10-21 DOI: 10.1145/2809563.2809596

K. Andrews, Thomas Traunmüller, Thomas Wolkinger, Robert Gutounig, Julian Ausserhofer

{"title":"Building an open data visualisation web app using a data server: the Styrian diversity visualisation project","authors":"K. Andrews, Thomas Traunmüller, Thomas Wolkinger, Robert Gutounig, Julian Ausserhofer","doi":"10.1145/2809563.2809596","DOIUrl":"https://doi.org/10.1145/2809563.2809596","url":null,"abstract":"Statistical open data is usually provided only in the form of spreadsheets or CSV files, which can sometimes be very large. The writer of an open data app is confronted with two choices: restrict themselves to managable bite-sized chunks of data, which can be consumed (read, parsed, and held in memory) in one go, or install and maintain their own data server which the app can query on demand. The Styrian Diversity Visualisation project was conceived to visualise the diversity of inhabitants of the Austrian Province of Styria (Land Steiermark) using open data served from a data server (triple store). The corresponding web app queries the data server at run rime with a SPARQL query to obtain exactly the data required at that particular time, greatly simplifying its internal logic. There is no need to parse and store entire data sets in memory. The data server is an instance of a Virtuoso Open Source server. The web app (client) is written in HTML5 and uses the leafletjs JavaScript library to provide mobile-friendly interactive maps. The user interface was designed as a set of three stories, each guiding users through a scenario with accompanying interactive visualisations based on corresponding open data sets.","PeriodicalId":20526,"journal":{"name":"Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79077977","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

Assistance- and knowledge-services for smart production 为智能生产提供援助和知识服务

Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business Pub Date : 2015-10-21 DOI: 10.1145/2809563.2809574

C. Ullrich, M. Aust, Niklas Kreggenfeld, Denise Kahl, Christopher Prinz, Simon Schwantzer

引用次数: 18

On big science: a survey 大科学:一项调查

Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business Pub Date : 2015-10-21 DOI: 10.1145/2809563.2809622

K. Delic, J. A. Riley

引用次数: 0

Process mining for knowledge-intensive business processes 知识密集型业务流程的流程挖掘

Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business Pub Date : 2015-10-21 DOI: 10.1145/2809563.2809580

Marian Benner-Wickner, Tobias Brückmann, V. Gruhn, Matthias Book

引用次数: 7

Advantages of extending wiki pages with knowledge-based recommendations 使用基于知识的推荐扩展wiki页面的优势

Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business Pub Date : 2015-10-21 DOI: 10.1145/2809563.2809611

Stefan Reiterer, Martin Stettinger, Michael Jeran, Wolfgang Eixelsberger, Manfred Wundara

引用次数: 0