Adaptive Linking between Text and Photos Using Common Sense

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Adaptive Linking between Text and Photos Using Common Sense (2002)

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by Henry Lieberman , Hugo Liu

Venue:	In Proceedings of the 2nd International Conference on Adaptive Hypermedia and Adaptive Web Based Systems, Malaga
Citations:	43 - 8 self

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@INPROCEEDINGS{Lieberman02adaptivelinking,
    author = {Henry Lieberman and Hugo Liu},
    title = {Adaptive Linking between Text and Photos Using Common Sense},
    booktitle = {In Proceedings of the 2nd International Conference on Adaptive Hypermedia and Adaptive Web Based Systems, Malaga},
    year = {2002},
    pages = {2--11},
    publisher = {Springer}
}

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Abstract

In a hypermedia authoring task, an author often wants to set up meaningful connections between different media, such as text and photographs. To facilitate this task, it is helpful to have a software agent dynamically adapt the presentation of a media database to the user's authoring activities, and look for opportunities for annotation and retrieval. However, potential connections are often missed because of differences in vocabulary or semantic connections that are "obvious" to people but that might not be explicit. In a hypermedia authoring task, an author often wants to set up meaningful connections between different media, such as text and photographs. To facilitate this task, it is helpful to have a software agent dynamically adapt the presentation of a media database to the user's authoring activities, and look for opportunities for annotation and retrieval. However, potential connections are often missed because of differences in vocabulary or semantic connections that are "obvious" to people but that might not be explicit. ARIA (Annotation and Retrieval Integration Agent) is a software agent that acts an assistant to a user writing e-mail or Web pages. As the user types a story, it does continuous retrieval and ranking on a photo database. It can use descriptions in the story to semi-automatically annotate pictures. To improve the associations beyond simple keyword matching, we use natural language parsing techniques to extract important roles played by text, such as "who, what, where, when". Since many of the photos depict common everyday situations such as weddings or recitals, we use a common sense knowledge base, Open Mind, to fill in semantic gaps that might otherwise prevent successful associations.

Keyphrases

software agent photo using common sense authoring activity meaningful connection different medium semantic connection medium database potential connection important role web page natural language retrieval integration agent open mind semi-automatically annotate picture simple keyword matching prevent successful association continuous retrieval common everyday situation common sense knowledge base semantic gap photo database

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