Demo Data from EDBT 2026 / reviewers in the wild / expert
Motoko Maki
dblp:14/9911
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information retrieval › query log analysis
clickthrough data |
0.1 | 1 | 2011 | Enhancing mobile search using web search log data · SIGIR 2011 |
Information retrieval › web search
mobile search |
0.1 | 1 | 2011 | Enhancing mobile search using web search log data · SIGIR 2011 |
Information retrieval
ranking |
0.1 | 1 | 2011 | Enhancing mobile search using web search log data · SIGIR 2011 |
Information retrieval › ranking
relevance estimation |
0.1 | 1 | 2011 | Enhancing mobile search using web search log data · SIGIR 2011 |
Information retrieval
web search |
0.1 | 1 | 2011 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2011 | Enhancing mobile search using web search log dataabstractMobile 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 |
SIGIR | 4 |