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Chunxin Xie

dblp:46/7115 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2009
—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 · 91% Recommender systems · 9%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval › search engines
desktop search
0.112009
Search your memory ! - an associative memory based desktop search system · SIGMOD Conference 2009
Information retrieval
retrieval models
0.112009
Search your memory ! - an associative memory based desktop search system · SIGMOD Conference 2009
Information retrieval
search engines
0.112009
Search your memory ! - an associative memory based desktop search system · SIGMOD Conference 2009
Recommender systems
personalized ranking
0.012009
Search your memory ! - an associative memory based desktop search system · SIGMOD Conference 2009

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

semantic link construction · 0.1personalized ranking · 0.1
YearPublicationVenuePosition
2009 Search your memory ! - an associative memory based desktop search system
abstract
We present XSearcher, an associative memory based desktop search system, which exploits associations by creating semantic links of personal desktop resources from explicit and implicit user activities. With these links, associations among memory fragments can be built or rebuilt in a user's brain during a search. The personalized ranking scheme uses these links together with a user's personal preferences to rank results by both relevance and importance. XSearcher enhances traditional keyword based search systems since it is closer to the way that human associative memory works.
Jidong Chen, Wentao Wu 0001, Chunxin Xie
SIGMOD Conference4