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Siyu Mi

dblp:71/8379 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2019
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Information retrieval · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval › user behavior › search behavior
click behavior
0.412019
Understanding the Interpretability of Search Result Summaries · SIGIR 2019
Information retrieval › search interfaces
search result presentation
0.412019
Understanding the Interpretability of Search Result Summaries · SIGIR 2019
Information retrieval › evaluation
user study
0.412019
Understanding the Interpretability of Search Result Summaries · SIGIR 2019
YearPublicationVenuePosition
2019 Understanding the Interpretability of Search Result Summaries
abstract
We examine the interpretability of search results in current web search engines through a lab user study. Particularly, we evaluate search result summary as an interpretable technique that informs users why the system retrieves a result and to which extent the result is useful. We collected judgments about 1,252 search results from 40 users in 160 sessions. Experimental results indicate that the interpretability of a search result summary is a salient factor influencing users' click decisions. Users are less likely to click on a result link if they do not understand why it was retrieved (low transparency) or cannot assess if the result would be useful based on the summary (low assessability). Our findings suggest it is crucial to improve the interpretability of search result summaries and develop better techniques to explain retrieved results to search engine users.
Siyu Mi, Jiepu Jiang
SIGIR1