PROJECTS

The research programme is structured in three scientific work packages, along the three groups of research objectives: WP1-Applications; WP2-Methods; WP3-Models. The programme is implemented via 15 Early Stage Researcher (ESR) projects, each primarily in one WP, but collaborating on the other two WPs. 8 of the 15 projects clearly identify one of the three application areas (innovation [I], healthcare [H], law [L]) while the remaining 7 projects provide horizontal links across domains and contribute to the harmonization of observations, cross-fertilisation of ideas, and identification of synergies between research groups, domains, and topics. The table below shows the list of ESR projects, with a brief description for each of them.

Primary Focus: Applications

ESR

Title

Brief Description

domain

Supervisor

RSR

Project 1: Rapid Systematic Reviews

Information extraction and assistance to the user for rapid understanding of difficult content and consequently rapid decision making towards systematic reviews of health documents.

H

Allan Hanbury (TUW)

AFS

Project 2: Applied Federated Innovation Search

Devise solutions for a federated patent search system for professional searchers and the whole spectrum of users searching for innovation-related information.

I

Michail Salampasis (IHU)

AC

Project 3: Augmenting Human Cognition Interfaces in the Workplace

Provide specifications for support tools to aid the user in analysing search results.

I

Elaine Toms (USFD)


IP

Project 4: Information in Production

Model information patterns and information flows in legal, intellectual property, and healthcare search, and use task contexts to correctly select and rank relevant entities and documents.

IHL

Allan Hanbury (TUW)

ES

Project 5: Configurable, Exploratory Search Interfaces

Provide support tools to aid the user in creating search and filtering pipelines for analysing results in the context of academic search.

I

Ian Ruthven (SUG)

GB

Project 6: Graph Browsing for Professional Search

Design, develop and evaluate graph browsing interfaces to browse through an organization’s knowledge graph and to cluster parts of the knowledge graph in coherent contexts and topics.

L

Suzan Verberne (ULEI)

Primary Focus: Methods

ESR

Title

Brief Description

domain

Supervisor

TUP

Project 7: Transparent User Profiling for Professional Search

Design and develop methods integrating models for user profiling and user behaviour based on the analysis of logs of search engine interactions.

L

Suzan Verberne (ULEI)

CIR

Project 8: Assessing Credibility, Value, and Relevance

Automatic or semi-automatic assessment of credibility of health-related user-generated content. 

H

Marco Viviani (UMB)

EM

Project 9: Identifying Work, Tasks, and Information Flows

Combine linked (open and closed) data, information extraction and dynamic workflows, to improve access to enterprise data in decision taking processes.

I

Arjen de Vries (SPQ)

TE

Project 10: Tasks in the Enterprise

Model work tasks to identify patterns of information need and use. 

IHL

Elaine Toms (USFD)

MCC

Project 11: Measuring and Modelling Cognitive Cost and Effort

Capture and reliably interpret costs/effort from implicit user signals measured from a range of sensors during an information seeking process.

IHL

Martin Halvey (SUG)

Primary Focus: Models

ESR

Title

Brief Description

domain

Supervisor

EMIS

Project 12: Economic Models of Interactive Search

Investigate and develop formal models for interactive Information Retrieval based on economic theory.

IHL

Leif Azzopardi (SUG)

KD

Project 13: Relevance Models based on Knowledge Delta

Determine relevance based on the difference in knowledge rather than similarity of query to document. 

IHL

Mihai Lupu (RSA)

DIR

Project 14: Decision Theoretic models for IR

Model Information Retrieval through techniques inspired by decision theory. 

IHL

Gabriella Pasi (UMB)

NNCS

Project 15: Neural Network Contextual Search

Analyse and evaluate representing the user and the user physical and cognitive context by neural network models

IHL

Gabriella Pasi (UMB)


This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860721