2012
DOI: 10.1007/978-3-642-33290-6_1
|View full text |Cite
|
Sign up to set email alerts
|

What Would ‘Google’ Do? Users’ Mental Models of a Digital Library Search Engine

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
19
0

Year Published

2013
2013
2023
2023

Publication Types

Select...
4
2
2

Relationship

0
8

Authors

Journals

citations
Cited by 22 publications
(19 citation statements)
references
References 21 publications
0
19
0
Order By: Relevance
“…Given what we know about the users' "folk models" for searching [3] (i.e., expected similarity to Web search engines), in this paper we demonstrate that more can be done to align our digital libraries with this type of mental model. Extending our previous work [1], we start by presenting some worked examples to highlight the ways in which user expectation and search interfaces can disconnect.…”
Section: Introductionmentioning
confidence: 71%
“…Given what we know about the users' "folk models" for searching [3] (i.e., expected similarity to Web search engines), in this paper we demonstrate that more can be done to align our digital libraries with this type of mental model. Extending our previous work [1], we start by presenting some worked examples to highlight the ways in which user expectation and search interfaces can disconnect.…”
Section: Introductionmentioning
confidence: 71%
“…With increasing efficiency, increased ease of use and more relevant results, scholarly search has become a far less frustrating experience. While Google is still perceived as the holy grail of discovery experiences, in reality it may not be quite what scholarly users are after [5]. The application of discovery layers has focused on eliminating the limitations that plagued the traditional federated search and improving the search index coverage and performance.…”
Section: Resultsmentioning
confidence: 99%
“…For instance, students and even librarians, struggle to understand what is being searched in each system and how results are ranked (See also [5]). …”
Section: Comparing Hta To a Usability Testmentioning
confidence: 99%
“…In the absence of good relevance ranking, too many results are as confusing as none at all (Khoo et al 2012); the number and ranking of results is central to search user experience.…”
Section: Typical Search Behaviourmentioning
confidence: 99%
“…Others posit that it is simply the way of things, and that the only way to combat it is to offer better information interfaces in libraries (Bell 2004). A recent study was able to identify the key ways in which Google outperforms traditional library interfaces (Khoo et al 2012); these include features like smart searching and 'did you mean' typographical error correction. By far the two most important features to users, however, were the single search box that searched 'everything' and the excellent relevance ranking Google offers; without this relevance ranking search tools were perceived to return 'too many' results.…”
Section: Academic Information Seeking and Googlementioning
confidence: 99%