Publication Type

Journal Article

Version

publishedVersion

Publication Date

11-2016

Abstract

Existing video search engines return a ranked list of videos for each user query, which is not convenient for browsing the results of query topics that have multiple facets, such as the "early life," "personal life," and "presidency" of a query "Barack Obama." Organizing video search results into semantically structured hierarchies with nodes covering different topic facets can significantly improve the browsing efficiency for such queries. In this paper, we introduce a hierarchical visualization approach for video search result browsing, which can help users quickly understand the multiple facets of a query topic in a very well-organized manner. Given a query, our approach starts from the hierarchy of its textual descriptions normally available onWikipedia and then adjusts the hierarchical structure by analyzing the video information to reflect the topic structure of the search result. After that, a simple optimization problem is formulated to perform the video-to-node association considering three important criteria. Furthermore, additional topic facets are mined to complement the contents of the existing semantic hierarchies. A large YouTube video dataset is constructed to evaluate our approach both quantitatively and qualitatively. A demo system is also developed for users to interact with the proposed browsing approach.

Keywords

Search result visualization, video search, hierarchical structure, visual analysis

Discipline

Databases and Information Systems | Graphics and Human Computer Interfaces

Research Areas

Intelligent Systems and Optimization

Publication

IEEE Transactions on Multimedia

Volume

18

Issue

11

First Page

2161

Last Page

2170

ISSN

1520-9210

Identifier

10.1109/TMM.2016.2614233

Publisher

Institute of Electrical and Electronics Engineers

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