Feedback Toolbox (full screen)

This toolbox contains information for students about how they can use feedback at the University of Southampton to improve their marks and enjoy their courses more. The toolbox also contains practical information about academic appeals, as well as a user's guide to delivering effective peer feedback.

Bias in the Social Web

Abstract A frequent assumption in Social Media is that its open nature leads to a representative view of the world. In this talk we want to consider bias occurring in the Social Web. We will consider a case study of liquid feedback, a direct democracy platform of the German pirate party as well as models of (non-)discriminating systems. As a conclusion of this talk we stipulate the need of Social Media systems to bias their working according to social norms and to publish the bias they introduce. Speaker Biography: Prof Steffen Staab Steffen studied in Erlangen (Germany), Philadelphia (USA) and Freiburg (Germany) computer science and computational linguistics. Afterwards he worked as researcher at Uni. Stuttgart/Fraunhofer and Univ. Karlsruhe, before he became professor in Koblenz (Germany). Since March 2015 he also holds a chair for Web and Computer Science at Univ. of Southampton sharing his time between here and Koblenz. In his research career he has managed to avoid almost all good advice that he now gives to his team members. Such advise includes focusing on research (vs. company) or concentrating on only one or two research areas (vs. considering ontologies, semantic web, social web, data engineering, text mining, peer-to-peer, multimedia, HCI, services, software modelling and programming and some more). Though, actually, improving how we understand and use text and data is a good common denominator for a lot of Steffen's professional activities.

PowerPoint document for GHCM Website (2016)

Resources created at University of Southampton for the module GIS for Health Care Management (GHCM)

Attachment files for GHCM Website (2016)

Resources created at University of Southampton for the module GIS for Health Care Management

3D_Relief_Displacement

Resources created at University of Southampton for the module Topographic Data Analysis

2D_Relief_Displacement

Resources created at University of Southampton for the module Topographic Data Analysis

Relief_Displacement_Example

Resources created at University of Southampton for the module Topographic Data Analysis

Relative_Orientation_Adjustment

Resources created at University of Southampton for the module Topographic Data Analysis

Slide_1

Resources created at University of Southampton for the module Topographic Data Analysis

Slide_2

Resources created at University of Southampton for the module Topographic Data Analysis

Orthorectification_Process

Resources created at University of Southampton for the module Topographic Data Analysis

Orthorectification

Resources created at University of Southampton for the module Topographic Data Analysis

Height_using_Parallax

Resources created at University of Southampton for the module Topographic Data Analysis

Groundxy_using_Parallax

Resources created at University of Southampton for the module Topographic Data Analysis

Data-Driven Text Generation using Neural Networks & Provenance is Complicated and Boring — Is there a solution?

Title: Data-Driven Text Generation using Neural Networks Speaker: Pavlos Vougiouklis, University of Southampton Abstract: Recent work on neural networks shows their great potential at tackling a wide variety of Natural Language Processing (NLP) tasks. This talk will focus on the Natural Language Generation (NLG) problem and, more specifically, on the extend to which neural network language models could be employed for context-sensitive and data-driven text generation. In addition, a neural network architecture for response generation in social media along with the training methods that enable it to capture contextual information and effectively participate in public conversations will be discussed. Speaker Bio: Pavlos Vougiouklis obtained his 5-year Diploma in Electrical and Computer Engineering from the Aristotle University of Thessaloniki in 2013. He was awarded an MSc degree in Software Engineering from the University of Southampton in 2014. In 2015, he joined the Web and Internet Science (WAIS) research group of the University of Southampton and he is currently working towards the acquisition of his PhD degree in the field of Neural Network Approaches for Natural Language Processing. Title: Provenance is Complicated and Boring — Is there a solution? Speaker: Darren Richardson, University of Southampton Abstract: Paper trails, auditing, and accountability — arguably not the sexiest terms in computer science. But then you discover that you've possibly been eating horse-meat, and the importance of provenance becomes almost palpable. Having accepted that we should be creating provenance-enabled systems, the challenge of then communicating that provenance to casual users is not trivial: users should not have to have a detailed working knowledge of your system, and they certainly shouldn't be expected to understand the data model. So how, then, do you give users an insight into the provenance, without having to build a bespoke system for each and every different provenance installation? Speaker Bio: Darren is a final year Computer Science PhD student. He completed his undergraduate degree in Electronic Engineering at Southampton in 2012.