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Bong-Jun Yi

dblp:82/8313 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2010
—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 · 56% Data mining · 44%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Data mining › text mining
information extraction and text analysis		 0.112010
Contextual video advertising system using scene information inferred from video scripts · SIGIR 2010
Information retrieval › online advertising › sponsored search
ad retrieval		 0.012010
Contextual video advertising system using scene information inferred from video scripts · SIGIR 2010

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

script-based inference · 0.1
YearPublicationVenuePosition
2010 Contextual video advertising system using scene information inferred from video scripts
abstract
With the rise of digital video consumptions, contextual video advertising demands have been increasing in recent years. This paper presents a novel video advertising system that selects relevant text ads for a given video scene by automatically identifying the situation of the scene. The situation information of video scenes is inferred from available video scripts. Experimental results show that the use of the situation information enhances the accuracy of ad retrieval for video scenes. The proposed system represents one of the pioneer video advertising systems using contextual information obtained from video scripts.
Bong-Jun Yi, Jung-Tae Lee, Hyun-Wook Woo, Hae-Chang Rim
 SIGIR1