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WebQuery: Searching and Visualizing the Web through Connectivity Jeromy Carriere, Nortel Rick Kazman, Software Engineering Institute 元智資工所 系統實驗室 楊錫謦 2000/1/5
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Outline Introduction System Description Visualization of Results Discussion Future Work & Conclusion
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Introduction Finding information located somewhere on the WWW is frequently a daunting task. Method: Yellow-pages content-based search tools Problems of the techniques above: vocabulary problem size of result
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Introduction(Cont.) One type of information we can use to tame the problems is : People form communities on the Web and reference each other.
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System Description Preprocessing phase The connectivity information is collected Run-time phase The result are fed into the VANISH tool.
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Visualization of Result “Rick Kazman”
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Visualization of Result(Cont.) “software engineering AND software architecture”
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Visualization of Result(Cont.) “library”
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Visualization of Result(Cont.) “back pain”
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Discussion to visualize large hit set – Cone Tree clutters to draw the user’s attension to the highly ranked nodes – bulleyes & springs-and-weights algorithms The springs-and-weights algorithms are expensive.
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Discussion(Cont.) WebQuery Weaknesses The result may contain nodes that are highly interlinked but represent a single repository of information. WebQuery has no knowledge of aliasing of Web sites or nodes.
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Future Work & Conclusion Future Work: Incorporation into the visualization such as the size of nodes, the correlation between keywords and nodes. a mechanism for aggregation of nodes in the visualization. WebQuery is powerful for searching the Web based on connectivity and content.
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Future Work & Conclusion(Cont.) Replace those visualization techniques with “Core Tree”: How to deal with focus changing? Loop Links
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