=Paper=
{{Paper
|id=Vol-2482/paper1
|storemode=property
|title=CIKM 2018 Workshops: Preface
|pdfUrl=https://ceur-ws.org/Vol-2482/paper1.pdf
|volume=Vol-2482
|authors=Alfredo Cuzzocrea,Francesco Bonchi,Dimitris Gunopulos
|dblpUrl=https://dblp.org/rec/conf/cikm/X18
}}
==CIKM 2018 Workshops: Preface==
CIKM 2018 Workshops: Preface Alfredo Cuzzocrea Francesco Bonchi Dimitris Gunopulos University of Trieste and ICAR-CNR ISI Foundation University of Athens Trieste, Italy Turin, Italy Athens, Greece alfredo.cuzzocrea@dia.units.it francesco.bonchi@isi.it dg@di.uoa.gr 1 Introduction “From Big Data and Big Information to Big Knowl- edge” has been the main theme of both CIKM 2018 This paper briefly introduces the workshops that have main conference and CIKM 2018 workshops. Indeed, been co-located with the 27th ACM International nowadays big data management and analytics (e.g., Conference on Information and Knowledge Manage- [ZE11, CCS12]), including advanced topics like knowl- ment (CIKM 2018), held during October 22-26, 2018 edge and information extraction from big data sources in Turin, Italy. (e.g., [BCC+ 14, WYC+ 13]) and privacy-preserving big CIKM 2018 selected 9 workshops, which have been data management (e.g., [CB11]), play a critical role, focused on several topics, all concerned with informa- and they are attracting the attention from the commu- tion and knowledge management in the big data era. nity more and more. Papers presented at these work- The CIKM 2018 workshop are listed in the following: shops have been focused on these topics mainly, with relevant proposals that span from theory to practice • DAB 2018 – 2018 Workshop on Data and Algo- and high-impact research project results. rithms Bias; The workshops have finally originated in some rele- vant questions that correspond to some open problems • DTMBio 2018 – 12th International Workshop on in big data management and analytics research. In the Data and Text Mining in Biomedical Informatics; following, we report on some among the most notice- able ones. • EYRE 2018 – 1st International Workshop on En- titY REtrieval ; Open Big Data Open big data define the manage- ment, mining and analytics of big data in the so-called • GLARE 2018 – 1st International Workshop on open environments (e.g., industry 4.0 settings), where GeneraLization in informAtion REtrieval ; (big) data can be exchanged among heterogeneous sys- tems, and analytics processes must be designed as to • KDAH 2018 – 2018 International Workshop on capture the peculiarities and the (business) goals of Knowledge-Driven Analytics Impacting Human the different environments, simultaneously. Quality of Life; Big Data Quality Big data quality refers to the issue • LeDAM 2018 – 2018 International Workshop on of understanding the quality of big data sources. This Legal DAta Mining; problem is strictly related to the so-called provenance problem (e.g., [CD18]). Indeed, when we process a • INRA 2018 – 6th International Workshop on big data source, usually we do not know the origin News Recommendation and Analytics; of such data, but simply use them. The challenge is thus determining models, techniques and algorithms • RDSM 2018 – 2nd International Workshop on Ru- to check about the quality of the (big) data source, in mours and Deception in Social Media; an automatic or semi-automatic manner. • SIR 2018 – 2018 International Workshop on So- Big Data in Emerging Domains The usage, pro- cial Interaction-based Recommendation. cessing and management of big data sources in emerg- Copyright © CIKM 2018 for the individual papers by the papers' ing domains, such as bio-medical systems, social net- authors. Copyright © CIKM 2018 for the volume as a collection works, sensor systems, and so forth, is, without doubts, by its editors. This volume and its papers are published under one of the most relevant challenges of future years, as the Creative Commons License Attribution 4.0 International (CC BY 4.0). practical issues pose the basis for relevant innovation in science and technology. We firmly hope that papers of the CIKM 2018 work- shops will represent a milestone in the exciting context of big data research. References [BCC+ 14] Peter Braun, Juan J. Cameron, Alfredo Cuzzocrea, Fan Jiang, and Carson Kai- Sang Leung. Effectively and efficiently mining frequent patterns from dense graph streams on disk. In 18th International Conference in Knowledge Based and Intel- ligent Information and Engineering Sys- tems, KES 2014, pages 338–347, 2014. [CB11] Alfredo Cuzzocrea and Elisa Bertino. Pri- vacy preserving OLAP over distributed XML data: A theoretically-sound secure- multiparty-computation approach. J. Comput. Syst. Sci., 77(6):965–987, 2011. [CCS12] Hsinchun Chen, Roger H L Chiang, and Veda C. Storey. Business intelligence and analytics: From big data to big impact. MIS Quarterly: Management Information Systems, 36(4):1165–1188, 2012. [CD18] Alfredo Cuzzocrea and Ernesto Damiani. Pedigree-ing your big data: Data-driven big data privacy in distributed environ- ments. In 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGRID 2018, Washington, DC, USA, May 1-4, 2018, pages 675–681, 2018. [WYC+ 13] Zhiang Wu, Wenpeng Yin, Jie Cao, Guan- dong Xu, and Alfredo Cuzzocrea. Com- munity detection in multi-relational social networks. In Web Information Systems Engineering - WISE 2013 - 14th Inter- national Conference, Nanjing, China, Oc- tober 13-15, 2013, Proceedings, Part II, pages 43–56, 2013. [ZE11] Paul Zikopoulos and Chris Eaton. Under- standing Big Data: Analytics for Enter- prise Class Hadoop and Streaming Data. McGraw-Hill Osborne Media, 1st edition, 2011.