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Details of Grant 

EPSRC Reference: EP/P024289/1
Title: Task Based Information Retrieval
Principal Investigator: Yilmaz, Dr E
Other Investigators:
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Department: Computer Science
Organisation: UCL
Scheme: EPSRC Fellowship
Starts: 01 September 2017 Ends: 31 August 2022 Value (£): 836,632
EPSRC Research Topic Classifications:
Information & Knowledge Mgmt
EPSRC Industrial Sector Classifications:
Information Technologies
Related Grants:
Panel History:
Panel DatePanel NameOutcome
22 Feb 2017 EPSRC ICT Fellowships Interview Panel Feb 2017 Announced
12 Jan 2017 EPSRC ICT Prioritisation Panel Jan 2017 Announced
Summary on Grant Application Form
The need for search often arises from a person's need to achieve a goal, or a task such as booking travels, buying a house, etc. Contemporary search engines focus on retrieving documents relevant to the query submitted as opposed to understanding and supporting the underlying information needs (or tasks) that have led a person to submit the query. Therefore, search engine users often have to submit multiple queries to the current systems to achieve a single information need.

Having identified that users often have to reformulate their queries in order to achieve their final goal, most current search engines attempt to assist users towards a better expression of their needs by suggesting queries to them, other than the query currently issued. However, query suggestions mainly focus on helping the user refine their current query, as opposed to helping them identify and explore aspects related to their current complex tasks. For example, when a user issues the query "flights to Barcelona", it is clear that the user is planning to travel to Barcelona and it is very likely that the user will also need to search for hotels in Barcelona or for shuttles from Barcelona airport. Since query suggestions mainly focus on refining the current query, suggestions provided by commonly used search engines are mostly of the form "flights to Barcelona from LOCATION", or "FLIGHT-CAREER-NAME flights to Barcelona" and the result pages provided by these systems do not contain any information that could help users book hotels or shuttles from the airport.

For very common tasks such as arranging travels, it may be possible to manually identify and guide the user through a list of (sub)tasks that need to be achieved in order to complete a certain task (booking a flight, finding a hotel, looking for points of interest, etc. when the user tries to arrange travel). However, given the variety of tasks search engines are used for, this would only be possible for a very small subset of them.

Furthermore, quite often search engines are used for achieving such complex tasks that often the searcher themself lacks the task knowledge necessary to decide which step to tackle next. For example, a searcher looking for information about how to maintain a car with no prior knowledge would first need to use the search engine to identify the parts of the car that need maintenance and issue separate queries to learn about maintaining each part. Hence, retrieval systems that can automatically detect the task the user is trying to achieve and guide them through the process are needed, where a search task has been previously defined as an atomic information need that consists of a set of related (sub)tasks.

Even though designing information retrieval (IR) systems that can characterize/identify tasks, and can respond to them efficiently is listed as one of the grand challenges in information retrieval, very little progress has been made in this direction. The main goal of this proposal is to devise task oriented retrieval systems, retrieval systems that can automatically detect the task that the user is trying to achieve and guide them through the process (steps) needed to achieve the task.

Key Findings
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Potential use in non-academic contexts
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