The University of Stavanger invites applications for two doctorate scholarship in information technology at Department of Electrical Engineering and Computer Science. The positions will be in context of the FAETE (From Answering Engines to Task-completion Engines) project starting in September 2015.
Details and application instructions: http://www.jobbnorge.no/en/available-jobs/job/115069/research-fellow-st-id-30061712-713
Application deadline: August 3, 2015.
Project description
Web search engines over the past decade have evolved into being the primary gateways to accessing the ever-growing amount of data available online. Major web search engines (Google, Bing, and Yahoo!) have become extremely effective in responding to a range of requests directly and appropriately (e.g., by showing results on a map or displaying "info-boxes" for entities, such as people or organizations). Search, however, is rarely performed for its own sake, but is usually associated with a specific target or goal. In many cases, this goal is the completion of a larger task, which is often complex (involving a nontrivial sequence of steps) and knowledgeintensive (requiring access to and manipulation of large quantities of information). Planning a family vacation or setting up a task force are just two of a plethora of examples. Such tasks call for a potentially large number of search queries to be issued in order to collect all the information needed. And, it often takes additional data processing steps (filtering, sorting, aggregating) before an actionable decision can be reached. Contemporary search environments are tailored to support a small set of basic search tasks and provide limited help in this tedious process. Resolving complex tasks with current search technology often requires us to use multiple search sessions and multiple search strategies, and then manually synthesize and integrate information across sessions (i.e., opening multiple windows or tabs and cutting-and-pasting information between them). To solve these problems, one needs a paradigm shift from answering engines to taskcompletion engines.
The aim of this project is to develop, implement, and test a task-completion engine that supports humans in solving complex, knowledgeintensive tasks, by providing an integrated environment that caters for all task-related activities (which, to date, are performed using a combination of various tools, applications, and services). Our system will provide assistance for formulating information needs by engaging in a dialog with the user, will offer rich interaction with results, and will be able to learn from past user interactions.
One PhD position will be focusing on user aspects: understanding and modeling user behavior and information needs in a task-based context, studying user interactions, and developing effective interfaces.
The other PhD position is focused on system aspects: understanding and representing information requests, and satisfying them by retrieving, extracting, and integrating information from various sources.
For further information regarding these positions, please contact Krisztian Balog (krisztian.balog@uis.no)
Details and application instructions: http://www.jobbnorge.no/en/available-jobs/job/115069/research-fellow-st-id-30061712-713
Application deadline: August 3, 2015.
Project description
Web search engines over the past decade have evolved into being the primary gateways to accessing the ever-growing amount of data available online. Major web search engines (Google, Bing, and Yahoo!) have become extremely effective in responding to a range of requests directly and appropriately (e.g., by showing results on a map or displaying "info-boxes" for entities, such as people or organizations). Search, however, is rarely performed for its own sake, but is usually associated with a specific target or goal. In many cases, this goal is the completion of a larger task, which is often complex (involving a nontrivial sequence of steps) and knowledgeintensive (requiring access to and manipulation of large quantities of information). Planning a family vacation or setting up a task force are just two of a plethora of examples. Such tasks call for a potentially large number of search queries to be issued in order to collect all the information needed. And, it often takes additional data processing steps (filtering, sorting, aggregating) before an actionable decision can be reached. Contemporary search environments are tailored to support a small set of basic search tasks and provide limited help in this tedious process. Resolving complex tasks with current search technology often requires us to use multiple search sessions and multiple search strategies, and then manually synthesize and integrate information across sessions (i.e., opening multiple windows or tabs and cutting-and-pasting information between them). To solve these problems, one needs a paradigm shift from answering engines to taskcompletion engines.
The aim of this project is to develop, implement, and test a task-completion engine that supports humans in solving complex, knowledgeintensive tasks, by providing an integrated environment that caters for all task-related activities (which, to date, are performed using a combination of various tools, applications, and services). Our system will provide assistance for formulating information needs by engaging in a dialog with the user, will offer rich interaction with results, and will be able to learn from past user interactions.
One PhD position will be focusing on user aspects: understanding and modeling user behavior and information needs in a task-based context, studying user interactions, and developing effective interfaces.
The other PhD position is focused on system aspects: understanding and representing information requests, and satisfying them by retrieving, extracting, and integrating information from various sources.
For further information regarding these positions, please contact Krisztian Balog (krisztian.balog@uis.no)
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