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Motoko Maki

dblp:14/9911 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2011
—ORCID · none

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

Databases, data management, data science and information retrieval · 1

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 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval › query log analysis
clickthrough data
0.112011
Enhancing mobile search using web search log data · SIGIR 2011
Information retrieval › web search
mobile search
0.112011
Enhancing mobile search using web search log data · SIGIR 2011
Information retrieval
ranking
0.112011
Enhancing mobile search using web search log data · SIGIR 2011
Information retrieval › ranking
relevance estimation
0.112011
Enhancing mobile search using web search log data · SIGIR 2011
Information retrieval
web search
0.112011
Enhancing mobile search using web search log data · SIGIR 2011

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

transfer learning · 0.1click-through data · 0.1
YearPublicationVenuePosition
2011 Enhancing mobile search using web search log data
abstract
Mobile search is still in infancy compared with general purpose web search. With limited training data and weak relevance features, the ranking performance in mobile search is far from satisfactory. To address this problem, we propose to leverage the knowledge of Web search to enhance the ranking of mobile search. In this paper, we first develop an equivalent page conversion between web search and mobile search, then we design a few novel ranking features, generated from the click-through data in web search, for estimating the relevance of mobile search. Large scale evaluations demonstrate that the knowledge from web search is quite effective for boosting the relevance of ranking on mobile search.
Yoshiyuki Inagaki, Jiang Bian 0002, Yi Chang 0001, Motoko Maki
SIGIR4