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When people encounter unfamiliar words, they often use tools such as search engines to obtain background information on these words. However, the semantic content of words can be complex, and it is not always possible to understand the meaning of words from textual information alone. In this paper we quantify the semantic content of words by means of a simple and convenient text-based method whereby the semantic content is constructed from linguistic, visual and auditory characteristic values. Using characteristic vectors generated in this way, users are able to visually check and search for background information on unfamiliar terms in a web document.

VISUALIZATION OF AND RETRIEVAL OF BACKGROUND INFORMATION RELATING TO WORDS IN WEB DOCUMENTS - A Visualization Interface based on Vector Representation