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An Analytical Inspection Framework for Evaluating the Search Tactics and User Profiles Supported by Information Seeking Interfaces

Max Wilson

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Swansea University Author: Max Wilson

Abstract

Searching is something we do everyday both in digital and physical environments. Whether we are searching for books in a library or information on the web, search is becoming increasingly important. For many years, however, the standard for search in software has been to provide a keyword search box...

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Published: 2009
Online Access: https://eprints.soton.ac.uk/69727/
URI: https://cronfa.swan.ac.uk/Record/cronfa189
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fullrecord <?xml version="1.0"?><rfc1807><datestamp>2017-11-22T16:14:45.6356422</datestamp><bib-version>v2</bib-version><id>189</id><entry>2011-10-01</entry><title>An Analytical Inspection Framework for Evaluating the Search Tactics and User Profiles Supported by Information Seeking Interfaces</title><swanseaauthors><author><sid>db09b25311e519f00542f3578cb5503e</sid><firstname>Max</firstname><surname>Wilson</surname><name>Max Wilson</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2011-10-01</date><abstract>Searching is something we do everyday both in digital and physical environments. Whether we are searching for books in a library or information on the web, search is becoming increasingly important. For many years, however, the standard for search in software has been to provide a keyword search box that has, over time, been embellished with query suggestions, Boolean operators, and interactive feedback. More recent research has focused on designing search interfaces that better support exploration and learning. Consequently, the aim of this research has been to develop a framework that can reveal to designers how well their search interfaces support different styles of searching behaviour.The primary contribution of this research has been to develop a usability evaluation method, in the form of a lightweight analytical inspection framework, that can assess both search designs and fully implemented systems. The framework, called Sii, provides three types of analyses: 1) an analysis of the amount of support the different features of a design provide; 2) an analysis of the amount of support provided for 32 known search tactics; and 3) an analysis of the amount of support provided for 16 different searcher profiles, such as those who are finding, browsing, exploring, and learning. The design of the framework was validated by six independent judges, and the results were positively correlated against the results of empirical user studies. Further, early investigations showed that Sii has a learning curve that begins at around one and a half hours, and, when using identical analysis results, different evaluators produce similar design revisions.For Search experts, building interfaces for their systems, Sii provides a Human-Computer Interaction evaluation method that addresses searcher needs rather than system optimisation. For Human-Computer Interaction experts, designing novel interfaces that provide search functions, Sii provides the opportunity to assess designs using the knowledge and theories generated by the Information Seeking community. While the research reported here is under controlled environments, future work is planned that will investigate the use of Sii by independent practitioners on their own projects.</abstract><type>Thesis</type><journal></journal><paginationStart>1</paginationStart><publisher/><keywords/><publishedDay>31</publishedDay><publishedMonth>12</publishedMonth><publishedYear>2009</publishedYear><publishedDate>2009-12-31</publishedDate><doi/><url>https://eprints.soton.ac.uk/69727/</url><notes>University of Southampton, Doctoral Thesis, School of Electronics and Computer Science.</notes><college>COLLEGE NANME</college><CollegeCode>COLLEGE CODE</CollegeCode><institution>Swansea University</institution><apcterm/><lastEdited>2017-11-22T16:14:45.6356422</lastEdited><Created>2011-10-01T00:00:00.0000000</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Mathematics and Computer Science - Computer Science</level></path><authors><author><firstname>Max</firstname><surname>Wilson</surname><order>1</order></author></authors><documents/><OutputDurs/></rfc1807>
spelling 2017-11-22T16:14:45.6356422 v2 189 2011-10-01 An Analytical Inspection Framework for Evaluating the Search Tactics and User Profiles Supported by Information Seeking Interfaces db09b25311e519f00542f3578cb5503e Max Wilson Max Wilson true false 2011-10-01 Searching is something we do everyday both in digital and physical environments. Whether we are searching for books in a library or information on the web, search is becoming increasingly important. For many years, however, the standard for search in software has been to provide a keyword search box that has, over time, been embellished with query suggestions, Boolean operators, and interactive feedback. More recent research has focused on designing search interfaces that better support exploration and learning. Consequently, the aim of this research has been to develop a framework that can reveal to designers how well their search interfaces support different styles of searching behaviour.The primary contribution of this research has been to develop a usability evaluation method, in the form of a lightweight analytical inspection framework, that can assess both search designs and fully implemented systems. The framework, called Sii, provides three types of analyses: 1) an analysis of the amount of support the different features of a design provide; 2) an analysis of the amount of support provided for 32 known search tactics; and 3) an analysis of the amount of support provided for 16 different searcher profiles, such as those who are finding, browsing, exploring, and learning. The design of the framework was validated by six independent judges, and the results were positively correlated against the results of empirical user studies. Further, early investigations showed that Sii has a learning curve that begins at around one and a half hours, and, when using identical analysis results, different evaluators produce similar design revisions.For Search experts, building interfaces for their systems, Sii provides a Human-Computer Interaction evaluation method that addresses searcher needs rather than system optimisation. For Human-Computer Interaction experts, designing novel interfaces that provide search functions, Sii provides the opportunity to assess designs using the knowledge and theories generated by the Information Seeking community. While the research reported here is under controlled environments, future work is planned that will investigate the use of Sii by independent practitioners on their own projects. Thesis 1 31 12 2009 2009-12-31 https://eprints.soton.ac.uk/69727/ University of Southampton, Doctoral Thesis, School of Electronics and Computer Science. COLLEGE NANME COLLEGE CODE Swansea University 2017-11-22T16:14:45.6356422 2011-10-01T00:00:00.0000000 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Max Wilson 1
title An Analytical Inspection Framework for Evaluating the Search Tactics and User Profiles Supported by Information Seeking Interfaces
spellingShingle An Analytical Inspection Framework for Evaluating the Search Tactics and User Profiles Supported by Information Seeking Interfaces
Max Wilson
title_short An Analytical Inspection Framework for Evaluating the Search Tactics and User Profiles Supported by Information Seeking Interfaces
title_full An Analytical Inspection Framework for Evaluating the Search Tactics and User Profiles Supported by Information Seeking Interfaces
title_fullStr An Analytical Inspection Framework for Evaluating the Search Tactics and User Profiles Supported by Information Seeking Interfaces
title_full_unstemmed An Analytical Inspection Framework for Evaluating the Search Tactics and User Profiles Supported by Information Seeking Interfaces
title_sort An Analytical Inspection Framework for Evaluating the Search Tactics and User Profiles Supported by Information Seeking Interfaces
author_id_str_mv db09b25311e519f00542f3578cb5503e
author_id_fullname_str_mv db09b25311e519f00542f3578cb5503e_***_Max Wilson
author Max Wilson
author2 Max Wilson
format Staff Thesis
container_start_page 1
publishDate 2009
institution Swansea University
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
url https://eprints.soton.ac.uk/69727/
document_store_str 0
active_str 0
description Searching is something we do everyday both in digital and physical environments. Whether we are searching for books in a library or information on the web, search is becoming increasingly important. For many years, however, the standard for search in software has been to provide a keyword search box that has, over time, been embellished with query suggestions, Boolean operators, and interactive feedback. More recent research has focused on designing search interfaces that better support exploration and learning. Consequently, the aim of this research has been to develop a framework that can reveal to designers how well their search interfaces support different styles of searching behaviour.The primary contribution of this research has been to develop a usability evaluation method, in the form of a lightweight analytical inspection framework, that can assess both search designs and fully implemented systems. The framework, called Sii, provides three types of analyses: 1) an analysis of the amount of support the different features of a design provide; 2) an analysis of the amount of support provided for 32 known search tactics; and 3) an analysis of the amount of support provided for 16 different searcher profiles, such as those who are finding, browsing, exploring, and learning. The design of the framework was validated by six independent judges, and the results were positively correlated against the results of empirical user studies. Further, early investigations showed that Sii has a learning curve that begins at around one and a half hours, and, when using identical analysis results, different evaluators produce similar design revisions.For Search experts, building interfaces for their systems, Sii provides a Human-Computer Interaction evaluation method that addresses searcher needs rather than system optimisation. For Human-Computer Interaction experts, designing novel interfaces that provide search functions, Sii provides the opportunity to assess designs using the knowledge and theories generated by the Information Seeking community. While the research reported here is under controlled environments, future work is planned that will investigate the use of Sii by independent practitioners on their own projects.
published_date 2009-12-31T03:02:58Z
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score 11.037603

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