Generating advertising keywords from video content

With the proliferation of online distribution methods for videos, content owners require easier and more effective methods for monetization through advertising. Matching advertisements with related content has a significant impact on the effectiveness of the ads, but current methods for selecting relevant advertising keywords for videos are limited by reliance on manually supplied metadata. In this paper we study the feasibility of using text available from video content to obtain high quality keywords suitable for matching advertisements. In particular, we tap into three sources of text for ad keyword generation: production scripts, closed captioning tracks, and speech-to-text transcripts. We address several challenges associated with using such data. To overcome the high error rates prevalent in automatic speech recognition and the lack of an explicit structure to provide hints about which keywords are most relevant, we use statistical and generative methods to identify dominant ...

• Type: Journal
• Year: 2010
• Where: CIKM
• Authors: Michael J. Welch, Junghoo Cho, Walter Chang
• Keywords: CIKM 2010, Information Technology, Keywords, Related Term Mining, Relevant Advertising Keywords