TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 12: User Intentions and Intentional Structures on the Web II

In this lecture, we will focus on analyzing user goals in search query logs. Readings: M. Strohmaier, P. Prettenhofer, M. Lux, Different Degrees of Explicitness in Intentional Artifacts - Studying User Goals in a Large Search Query Log, CSKGOI'08 International Workshop on Commonsense Knowledge and Goal Oriented Interfaces, in conjunction with IUI'08, Canary Islands, Spain, 2008.

TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 11: User Intentions and Intentional Structures on the Web

Search engines - such as Google - have been characterized as "Databases of intentions". This class will focus on different aspects of intentionality on the web, including goal mining, goal modeling and goal-oriented search. Readings: M. Strohmaier, M. Lux, M. Granitzer, P. Scheir, S. Liaskos, E. Yu, How Do Users Express Goals on the Web? - An Exploration of Intentional Structures in Web Search, We Know'07 International Workshop on Collaborative Knowledge Management for Web Information Systems in conjunction with WISE'07, Nancy, France, 2007. [Web link] Readings: Automatic identification of user goals in web search, U. Lee and Z. Liu and J. Cho WWW '05: Proceedings of the 14th International World Wide Web Conference 391--400 (2005) [Web link]

A user receiving help at Hartley Library reception desk 3

An image of a user receiving help at Hartley Library reception desk, taken 2009.

A user receiving help at Hartley Library reception desk 2

An image of a user receiving help at Hartley Library reception desk, taken 2009

A user receiving help at the subject enquiry desk

An image of a user sitting down while receiving help at the subject enquiry desk, taken 2009

A user receiving help at the Hartley Library reception desk 1

An image of a user receiving help at the Hartley Library reception desk, taken 2009

Team Working and Profiling Handout

Exercise and Handout for use in conjunction with Lecture on team working and profiling. Refers to Belbin model of team development. If you have missed the class, you should work through the activity, ideally find some other students to work with. It consists of a number of parts in addition to a self-evaluation checklist 1) A personal reflection activity (for use as the class settles) 2) A brief group activity to use during the lecture 3) A follow up activity, to complete an evaluation online from the belbin website 4) A follow up activity to work through the videos which have been produced by the LearnHigher Project

ELEC1032 Team Working and Profiling

Powerpoint Slide set used to manage in class activity based introduction to team profiling from the Belbin perspective.

Laser User Registration Form

Blank laser user registration form

Adobe Connect Quick User Guide for tutors

This brief guide (two sides of A4) is a reminder sheet for tutors and research staff who wish to hold meetings online using Adobe Connect

Adobe Connect Quick User Guide for Students

This one-side-of-A4 guide is a reminder of most of the things that students need to know to have meetings online.

Adobe Connect Quick User Guide to setting up your PC

This one-side-of-A4 guide discusses setting up your audio correctly and installing the Connect browser add-in.

Share Manager User Guide

This user guide outlines the functionality of the new Share Manager.

Team Working and Profiling

slides and accompanying handouts for hectic classroom activity bases session. See also notes on ECS module page: https://secure.ecs.soton.ac.uk/module/1617/COMP1205/33423/

A User-Centric Approach to eCertificate for Electronic Identities (eIDs) Management in Mobile Environment

The use of electronic documents is constantly growing and the necessity to implement an ad-hoc eCertificate which manages access to private information is not only required but also necessary. This paper presents a protocol for the management of electronic identities (eIDs), meant as a substitute for the paper-based IDs, in a mobile environment with a user-centric approach. Mobile devices have been chosen because they provide mobility, personal use and high computational complexity. The inherent user-centricity also allows the user to personally manage the ID information and to display only what is required. The chosen path to develop the protocol is to migrate the existing eCert technologies implemented by the Learning Societies Laboratory in Southampton. By comparing this protocol with the analysis of the eID problem domain, a new solution has been derived which is compatible with both systems without loss of features.