Zhe Xue
ABSTRACT
Although lots of work has been done since NIST proposed the problem of Topic Detection and Tracking (TDT), most of them focus on single media data. Topic detection for cross-media data hasn't been fully investigated. In this paper, we propose an effective method for cross-media topic detection. Unlike traditional topic detection methods that are mainly based on clustering, we consider using hot search queries as guidance to detect topics. Besides, we propose an improved co-clustering method which can be well suited for cross-media data clustering. First, we use queries to detect topics directly, and find the data associated with the topic. Second, we apply our co-clustering method to find the topics existing in the rest of data. Finally, the results obtained by the first two steps are threaded together as topics. Experiments show that our method can effectively detect topics for cross-media data.
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