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SUMMARYCreative activities based on combinations are now being carried on everywhere in the world. Whether or not the creative activity succeeds depends on the combinations used in it. Since there are tremendous numbers of candidate combinations, it is impossible to decide at a glance which should be used. Thus, there must be a method of efficiently discovering combinations which are effective in making creative activity a success. This paper proposes a method of discovering combinations that is effective in supporting creative activity. In the proposed method, the originality of each combination and the novelty perceived by users are estimated from the number of hits on Web pages containing the keywords in question, and the effectiveness of the combinations is judged.

SummaryThere are so many opportunities to transmit text information on the Web. Since texts on the Web are not always written by professional writers, those may not be coherent or may be hard to be comprehended. Therefore, we should take too much time and energy to grasp topic relevance of a text.This paper describes HINATA system that visualizes texts using light and shadow based on topic relevance. Topic is defined as a set of words such as nouns contained in a title of a text. The light expresses sentences related to a topic, and the shadow expresses sentences unrelated to a topic. This visualization method efficiently supports users for finding the parts related to a topic, and for grasping relations between sentences of a text and a topic. Experimental results showed that the proposed system could support users for understanding how a text was related to a topic.

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SUMMARYThe information displayed as the search result by search engines is important for quickly finding the desired information. In particular, the summary of each Web page in the search results is important for determining the Web page content, as well as for determining how the input search term is used in each Web page, namely, the relation between the search term and the Web page. However, the summaries of the search results in conventional search engines have problems such as extracting only the opening text and not containing the search term, or containing the search term but having the sentence truncated in the middle so that the context of the term or the content of the Web page cannot be determined. Therefore, a summary in sentence units is desirable, but since HTML text includes many nonsentence items that do not contain punctuation, if they are unprocessed, it is difficult for a key sentence extraction system that treats sentences as units to provide a summary. Thus, in this paper, we propose an HTML text segmentation system that divides the source text of each Web page into meaningfully connected groups of text corresponding to sentences. We also verify experimentally that the text generated by this system can be used effectively in a Web page summarization.