In this project we investigate searching and browsing in social sites and determine where the one-shot and one-size-fits-all paradigm of search is failing users and does not sufficiently assist them with their information gathering task. We use modern statistical learning techniques to develop models that are able to utilise personalisation, temporal task-based knowledge and topical information derived from the corpus to improve search. The proposed work significantly extend earlier work in personalisation of social media search and latent topic models carried out by the applicant.
Current Projects
This COST Action explores innovative frameworks to empower the synergies from the disparate research fields of Machine Translation, Information Retrieval and Multifaceted Interactive Information Access within the specific context of patent search and other next generation Web applications. See here for more information.
HEBE -Highly Engaging e-Book Experiences- aims at producing novel interfaces for playing, interacting and reading e-books for children. We propose in this study to involve children in exploring different type of technology, hardware and software, in order to produce more engaging, usable and fun e-book interfaces for them. The main hypothesis of the study is that in order to make e-reading a fun experience for children new innovative interfaces are needed and children should take an active role in their design.
This collaborative project with AT&T Labs deals with designing, implementing and evaluation new mobile interfaces for information retrieval. In particular, in this project we are developing a Just-in-Time Mobile Information Retrieval (JIT-MobIR) system. The system is able to predict user actions and needs and generate appropriate queries to find the information before the user actually knows he needs it.
In this project we will extend the latest models of statistical content analysis, that are proving successful in the areas of text mining and information retrieval, for the mining of conversational content for topic identification (what is the conversation about?) and author identification (who are the people involved in the conversation?).
The project has two different but integrated objectives. The first is to study how selected categories of users search for patents in relation to specific information needs and tasks. This will result in a set of guidelines to drive the design of innovative and more usable interactive systems for patent search. The second objective is to use these guidelines for the design and implementation of a new interactive patent search system that will then be evaluated with real users in the context of real search tasks, using a user and task oriented evaluation methodology. The emphasis in both objectives is on interactivity.