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Michael A. S. Potts

dblp:36/7020 · also Michael Alan Sherred Potts · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2007
—ORCID · none

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

Databases, data management, data science and information retrieval · 2

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
2 papers
Information retrieval · 100%

Topics — the 6 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval
query log analysis
0.122007
Information re-retrieval: repeat queries in Yahoo's logs · SIGIR 2007
History repeats itself: repeat queries in Yahoo's logs · SIGIR 2006
Information retrieval › interactive information retrieval › search tasks
re-finding
0.122007
Information re-retrieval: repeat queries in Yahoo's logs · SIGIR 2007
History repeats itself: repeat queries in Yahoo's logs · SIGIR 2006
Information retrieval › query log analysis
repeat query
0.122007
Information re-retrieval: repeat queries in Yahoo's logs · SIGIR 2007
History repeats itself: repeat queries in Yahoo's logs · SIGIR 2006
Information retrieval
user behavior
0.122007
Information re-retrieval: repeat queries in Yahoo's logs · SIGIR 2007
History repeats itself: repeat queries in Yahoo's logs · SIGIR 2006
Information retrieval
evaluation
0.012007
Information re-retrieval: repeat queries in Yahoo's logs · SIGIR 2007
Information retrieval
search engines
0.012006
History repeats itself: repeat queries in Yahoo's logs · SIGIR 2006

Methods — techniques the papers use, named apart from their topics

survey · 0.1query log analysis · 0.1
YearPublicationVenuePosition
2007 Information re-retrieval: repeat queries in Yahoo's logs
abstract
People often repeat Web searches, both to find new information on topics they have previously explored and to re-find information they have seen in the past. The query associated with a repeat search may differ from the initial query but can nonetheless lead to clicks on the same results. This paper explores repeat search behavior through the analysis of a one-year Web query log of 114 anonymous users and a separate controlled survey of an additional 119 volunteers. Our study demonstrates that as many as 40% of all queries are re-finding queries. Re-finding appears to be an important behavior for search engines to explicitly support, and we explore how this can be done. We demonstrate that changes to search engine results can hinder re-finding, and provide a way to automatically detect repeat searches and predict repeat clicks.
Jaime Teevan, Eytan Adar, Rosie Jones, Michael A. S. Potts
SIGIR4
2006 History repeats itself: repeat queries in Yahoo's logs
abstract
Thanks to the ubiquity of the Internet search engine search box, users have come to depend on search engines both to find and re-find information. However, re-finding behavior has not been significantly addressed. Here we look at re-finding queries issued to the Yahoo! search engine by 114 users over a year.
Jaime Teevan, Eytan Adar, Rosie Jones, Michael A. S. Potts
SIGIR4