Carl L. Sable

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Recently, there have been significant advances in several areas of language technology, including clustering, text categorization, and summarization. However, efforts to combine technology from these areas in a practical system for information access have been limited. In this paper, we present Columbia's Newsblaster system for online news summarization.(More)
The rapid expansion of multimedia digital collections brings to the fore the need for classifying not only text documents but their embedded non-textual parts as well. We propose a model for basing classification of multimedia on broad, non-topical features, and show how information on targeted nearby pieces of text can be used to effectively classify(More)
The rapid expansion of multimedia digital collections brings to the fore the need for classifying not only text documents but their embedded non-textual parts as well. We propose a model for basing classification of multimedia on broad, non-topical features, and show how information on targeted nearby pieces of text can be used to effectively classify(More)
Annotating photographs automatically with content descriptions facilitates organization, storage, and search o ver visual information. We present a n i n tegrated approach for scene classiication that combines image-based and text-based approaches. On the text side, we use the text accompanying an image in a n o vel TF*IDF vector-based approach to(More)
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