ACM CIKM 2016 Workshops
We are happy to announce that the following workshops will be held at CIKM 2016:
The theme of cybersafety is an important emerging research topic on the Internet that manifests itself daily as users navigate the Web and networked applications. Examples of cybersafety issues include cyberbullying, cyberthreats, recruiting minors via Internet services for nefarious purposes, using deceptive means to dupe vulnerable populations, exhibiting misbehaving behaviors such as using profanity or flashing in online video chats, and many others. These issues have a direct negative impact on the social, psychological and in some cases physical well-being of the end users. An important characteristic of these issues is that they fall in a grey legal area, where perpetrators may claim freedom of speech or rights to free expression despite causing harm. The main goal of this inaugural workshop on cybersafety is to bring together the researchers and practitioners from academia, industry, government and research labs working in the area of cybersafety to discuss the unique challenges in addressing various cybersafety issues and to share experiences, solutions, tools, and techniques. The focus is on the detection, prevention and mitigation of various cybersafety issues, as well as education and promoting safe practices.
The proliferation of social media platforms together with the wide adoption of smartphone devices has transformed how we communicate and share news. During large-scale emergencies, such as natural disasters or armed attacks, victims, responders, and volunteers increasingly use social media
to post situation updates and to request and offer help. The use of social media for emergency and disaster response has been a prominent application of information and knowledge management techniques in recent years. There are a number of challenges associated with near-realtime processing of vast volumes of information in a way that makes sense for people directly affected, for volunteer organizations, and for official emergency response agencies. As massive amount of messages posted by users are transformed into semi-structured records via information extraction and natural language processing techniques, there is a growing need for developing advanced techniques to aggregate this large-scale data to gain an understanding of the “big picture” of an emergency, and to detect and predict how a disaster could develop. This workshop seeks to provide a platform for the exchange of ideas, identification of important problems, and discovery of possible synergies. It will enable interesting discussions and encouraged collaboration between various disciplines, and information and knowledge management approaches is the core of this workshop.
Our world is networked: people are closer to each other through online social network services or mobile communication networks, while information is capable to be exchanged faster by World Wide Web or email networks. The network is a treasure trove of user experiences and knowledge that presents great opportunities to understand the fundamental science of our world. On the other hand, the network, with huge amount of data, and multiple types of entities (e.g., users, documents, organizations, etc.), user behaviors, and relations between entities, has become so large and complex that traditional methodologies are inadequate. This workshop aims to provide a forum for presenting the most recent advances in mining big networks to unearth rich knowledge. We expect novel research works that address various aspects of large network analysis, including data acquisition and integration, novel applications in different problem domains, scalable and efficient network analytic algorithms, distributed network data management, novel platforms supporting network analytics, and so on.
People search is a well-established field in information retrieval. With the TREC Enterprise Track in 2005 there was an early focus on the enterprise setting. In recent years, the increasing availability of data enables accumulation of evidence of talent and expertise from a wide range of domains beyond the enterprise. The availability of big data significantly benefits employers and recruiters. By analyzing the massive amounts of structured and unstructured data, organizations may be able to find the exact skillsets and talent they need to grow their business. The aim of this workshop is to provide a forum for industry and academia to discuss the recent progress in talent search and how the use of big data and data-driven decision making can advance talent acquisition.
The world is awash with big data now – we are generating ten exabytes of data in a variety of different forms every day. In this wave, there is a trend to integrate the data mining methods with interactive visualizations to advance the so-called visual analytics (VA) technology. The VA technique enjoys the joint advantage of the human intelligence and the machine’s computational power. Various aspects of the data mining method need to be inspected, justified, organized and evaluated for a successful VA system. The challenges include but not limited to the data reduction, integration, governance and knowledge representation. Exploring all these directions for joining the data analysis with visualization and finally delivering values to users is a problem of vital importance and requires a lot of efforts from different parties where information management researchers from both data mining and visualization play major roles. This makes the workshop highly relevant to CIKM, the premier international conference on topics at the confluence of information retrieval, databases, and knowledge management. Moreover, the National Science Foundation of United States sets up a continuous program on the foundation of data and visual analytics, the FODAVA1, which makes this workshop an in-time event for people to share their opinions and experiences on this topic.
The rapid development of medical and health informatics techniques is tightly coupled with developments within several fields in computer science, including data and text mining, information retrieval, information extraction and database management systems, among others. A fundamental topic of research within medical and healthcare informatics is how to make effective use of the tremendous amount of biological and biomedical data to improve the understanding of biological systems. Such data include, but are not limited to, gene and protein sequences, gene expression profiles from Microarray experiments, protein structure predictions resulting from high-throughput computational methods, protein-protein interactions from proteomic studies, Single Nucleotide Polymorphisms profiles from SNP arrays, and information from the literature and other textual resources. The need to extract, understand, integrate, and make use of information embedded in such heterogeneous unstructured data, automatically and effectively drives the current research in medical and healthcare informatics. The focus of this workshop is to bring together researchers that work in the areas of data and text mining and computational biology, interested in integrating such heterogeneous structured and unstructured data, while effectively using literature information in medical and healthcare informatics solutions.