The first day of the conference comprises a range of workshops, to be held on Tuesday 10th December. Delegates will find these events to be especially valuable where there is a current need to consider the introduction of new AI technologies into their own organisations.
There will be four half-day workshops plus an all-day workshop, the Eighteenth UK CBR Workshop. Delegates are free to choose any combination of morning and afternoon sessions to attend. The programme of workshops is shown below. Note that the morning session starts at 11 a.m. to reduce the need for delegates to stay in Cambridge on the previous night. There is a lunch break from 12.30-13.15 and there are refreshment breaks from 14.45-15.15 and from 16.45-17.00.
Workshops organiser: Professor Adrian Hopgood, Sheffield Hallam University
Stream 1 - Morning (11.00-12.30 and 13.15-14.45 Upper Hall)
Visual Analytics - Present and Future of Human-Computer Interaction in Data Analytics
Chair: Dr Martin Spott, BT Research and Innovation, Ipswich, UK
Data Analytics promises to give organisations more insight into internal processes, their customers' behaviour and new market opportunities. Though they collect more and more of an increasing flow of data, organisations are still struggling to harvest knowledge from it. Where reporting based on data is the norm and accessible by most employees, deep analyses of data can only be conducted by specialists and even they are let down by software tools that are more awkward to use than necessary. The lasting popularity of spreadsheet software is therefore not surprising despite its severe limitations.
In recent years, often associated with the term Big Data, the granularity of data has been changing from a natural chunk size like transactions to ubiquitous sensor readings and micro events that, in isolation, bear no meaning or relevance. Turning masses of such granular data into actionable information requires an understanding of context and relationships such that they can be aggregated and combined into meaningful chunks. Machine Learning can find structures, but they may not be meaningful. Data Scientists can provide domain knowledge, use human pattern recognition on data visualisation and think out of the box, but they can hardly scratch the sheer volume of data points and their combinations.
The aim of this workshop is to present and discuss existing approaches and the future of human-computer interaction in data analytics. The right symbiosis will make use of the ever increasing computational power of computers combined with the creativity and knowledge of data scientists and domain experts. The workshop will cover aspects of machine learning, data and pattern visualisation, human-computer interaction and touch on the process of designing an interface for end users. The applications may vary across the overall process of data analysis: from joining, cleaning, pre-processing and transforming data over pattern discovery to decision support.
Stream 1 - Afternoon (15.15-16.45 and 17.00-18.30 Upper Hall)
Big Data for AI
Co-chair: Dr Simon Thompson, BT Research and Innovation, Ipswich, UK
Big Data technology like Hadoop supports a number of novel components for handling and processing large volumes of complex, poly-structured data. For example the Hive massively parallel SQL data warehouse, HBase for parallel No-SQL and the Map-Reduce or YARN frameworks for distributed programming. Hadoop enables the application of the vast processing and storage power created by the march of Moore's law to be easily and cheaply accessed.
However, traditionally AI has been plagued by computational problems in planning, vision and speech transcription (for example); are there opportunities to apply Hadoop and associated technologies in these domains?
This workshop has three objectives :
Follow the workshop blog.
Submission deadline: October 7th 2013.
Stream 2 - Morning (11.00-12.30 and 13.15-14.45 Lubbock Room)
Social Media Analysis
Co-chair: Dr Mohamed Medhat Gaber, Robert Gordon University, UK
Social media websites such as Twitter, Facebook, Instagram, and YouTube continue to share user-generated content on a massive scale. User’s attempting to find relevant information within such vast and dynamic volumes risk being overwhelmed. In response, efforts are being made to develop new tools and methods that help users make sense of – and make use of – social media sites. In this workshop we will bring together commercial and academic researchers to discuss these issues, and explore the challenges for social media mining.
The current expansion of social media leads to masses of affective data related to peoples’ emotions, sentiments and opinions. Knowledge discovery from such data is an emerging area of research in the past few years, with a potential number of applications of paramount importance to business organisations, individual users and governments. Data mining and machine learning techniques are used to discover knowledge from various types of affective data such as ratings, text or browsing data. Although research in this area has grown considerably in the recent years, knowledge discovery from affective data is in its infancy state with more open issues and challenges which often requires interdisciplinary approaches.
This workshop aims to bring together researchers in this area to present their latest work, to discuss the challenges in the field and identify where our efforts, as a research community, should focus.
Topics of interest:
Stream 2 - Afternoon (15.15-16.45 and 17.00-18.30 Lubbock room)
Computational Optimisation for Practical Applications
Chair: Prof Dr Lars Nolle, Jade Hochschule/University of Applied Science, Germany
In today's modern life, there is an ever-increasing demand for intelligent systems, i.e. systems that can learn and adapt to changing environments. This intelligent behaviour can be achieved by tuning internal models of a system so that they fit the observations better. In other words, intelligent systems learn and adapt by searching for optimal model parameters.
This workshop will provide insight into computational search and optimisation techniques with a particular view on their practical application; we will have a closer look at the different types of optimisation problems and their complexity. We will discuss the pros and cons of traditional algorithms and modern meta-heuristics. We will also see examples of their application to real-world problems.
The goal of the workshop is to make practitioners aware of the opportunities offered by computational optimisation methods and to provide them with practical guidelines to apply them to real-world problems.
Stream 3 - All Day (11.00-12.30, 13.15-14.45, 15.15-16.45 and 17.00-18.30 Peterhouse Lecture Theatre)
Eighteenth UK Case-Based Reasoning workshop
Chair: Professor Miltos Petridis, University of Brighton