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An Integrated Model of Tasks and Uncertainties for Designing Task-aware Search Assistants- [electronic resource]
An Integrated Model of Tasks and Uncertainties for Designing Task-aware Search Assistants- [electronic resource]
상세정보
- 자료유형
- 학위논문파일 국외
- 최종처리일시
- 20240214101250
- ISBN
- 9798380327268
- DDC
- 020
- 저자명
- Sarkar, Shawon.
- 서명/저자
- An Integrated Model of Tasks and Uncertainties for Designing Task-aware Search Assistants - [electronic resource]
- 발행사항
- [S.l.]: : University of Washington., 2023
- 발행사항
- Ann Arbor : : ProQuest Dissertations & Theses,, 2023
- 형태사항
- 1 online resource(237 p.)
- 주기사항
- Source: Dissertations Abstracts International, Volume: 85-03, Section: B.
- 주기사항
- Advisor: Shah, Chirag.
- 학위논문주기
- Thesis (Ph.D.)--University of Washington, 2023.
- 사용제한주기
- This item must not be sold to any third party vendors.
- 초록/해제
- 요약Search behaviors are usually motivated by some task that prompts users into the search process. Complex tasks often initiate long, evolving, interactive search processes with shifting goals and cognitive focus at different search stages. Users' search strategies are influenced by their search motivation, encountered problems, and cognitive focus or state of knowledge at these search stages. However, existing search systems are primarily designed to optimize one request at a time, ignoring the underlying overarching task, shifting task phases and subtasks with users' cognitive focus, or even the holistic nature of a task-based search session. Although a set of descriptive and theoretical models of the search process can be found in the literature that characterizes tasks, there is a gap in research focused on exploiting dynamic task characteristics in search personalization processes. More importantly, there is a lack of support for users to complete their tasks in an adaptive, dynamic way. To address this issue, this dissertation adopts a multi-disciplinary, human-centered approach and applies a mixed-methods design-based approach to meet three broad objectives: first, develop a conceptual framework for understanding how different types of tasks trigger specific information needs that can lead to different methods and strategies for seeking different forms of information and information sources and, in the due process, identify any barriers they perceive and potential help they choose to overcome those limitations; second, apply new computational models to construct unified task representations using underlying search behavioral signals that can be transferable and functional to any task circumstances; and Third make existing search and retrieval systems more responsible and efficient to meet the changing state of users' cognitive focus during the search process by using knowledge gained about users' tasks and problems. Specifically, this dissertation aims to develop a task-information need-strategy-problem-based task representation that can be leveraged in search and retrieval models to provide task-based supports in different information formats, thus empowering users to make informed decisions about different aspects of their lives by providing information more relevant to their current task state. The result of this study is a step towards developing task-aware intelligent systems capable of supporting users at each stage of their complex task-completion process.
- 일반주제명
- Information science.
- 일반주제명
- Computer engineering.
- 일반주제명
- Computer science.
- 일반주제명
- Information technology.
- 키워드
- Search tasks
- 키워드
- Task modeling
- 키워드
- Search behaviors
- 키워드
- Users
- 기타저자
- University of Washington Information School
- 기본자료저록
- Dissertations Abstracts International. 85-03B.
- 기본자료저록
- Dissertation Abstract International
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■020 ▼a9798380327268
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■1001 ▼aSarkar, Shawon.
■24513▼aAn Integrated Model of Tasks and Uncertainties for Designing Task-aware Search Assistants▼h[electronic resource]
■260 ▼a[S.l.]:▼bUniversity of Washington. ▼c2023
■260 1▼aAnn Arbor :▼bProQuest Dissertations & Theses, ▼c2023
■300 ▼a1 online resource(237 p.)
■500 ▼aSource: Dissertations Abstracts International, Volume: 85-03, Section: B.
■500 ▼aAdvisor: Shah, Chirag.
■5021 ▼aThesis (Ph.D.)--University of Washington, 2023.
■506 ▼aThis item must not be sold to any third party vendors.
■520 ▼aSearch behaviors are usually motivated by some task that prompts users into the search process. Complex tasks often initiate long, evolving, interactive search processes with shifting goals and cognitive focus at different search stages. Users' search strategies are influenced by their search motivation, encountered problems, and cognitive focus or state of knowledge at these search stages. However, existing search systems are primarily designed to optimize one request at a time, ignoring the underlying overarching task, shifting task phases and subtasks with users' cognitive focus, or even the holistic nature of a task-based search session. Although a set of descriptive and theoretical models of the search process can be found in the literature that characterizes tasks, there is a gap in research focused on exploiting dynamic task characteristics in search personalization processes. More importantly, there is a lack of support for users to complete their tasks in an adaptive, dynamic way. To address this issue, this dissertation adopts a multi-disciplinary, human-centered approach and applies a mixed-methods design-based approach to meet three broad objectives: first, develop a conceptual framework for understanding how different types of tasks trigger specific information needs that can lead to different methods and strategies for seeking different forms of information and information sources and, in the due process, identify any barriers they perceive and potential help they choose to overcome those limitations; second, apply new computational models to construct unified task representations using underlying search behavioral signals that can be transferable and functional to any task circumstances; and Third make existing search and retrieval systems more responsible and efficient to meet the changing state of users' cognitive focus during the search process by using knowledge gained about users' tasks and problems. Specifically, this dissertation aims to develop a task-information need-strategy-problem-based task representation that can be leveraged in search and retrieval models to provide task-based supports in different information formats, thus empowering users to make informed decisions about different aspects of their lives by providing information more relevant to their current task state. The result of this study is a step towards developing task-aware intelligent systems capable of supporting users at each stage of their complex task-completion process.
■590 ▼aSchool code: 0250.
■650 4▼aInformation science.
■650 4▼aComputer engineering.
■650 4▼aComputer science.
■650 4▼aInformation technology.
■653 ▼aInteractive information retrieval
■653 ▼aSearch tasks
■653 ▼aTask modeling
■653 ▼aSearch behaviors
■653 ▼aUsers
■690 ▼a0723
■690 ▼a0489
■690 ▼a0984
■690 ▼a0464
■71020▼aUniversity of Washington▼bInformation School.
■7730 ▼tDissertations Abstracts International▼g85-03B.
■773 ▼tDissertation Abstract International
■790 ▼a0250
■791 ▼aPh.D.
■792 ▼a2023
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16933472▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a202402▼f2024
