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

Outline Introduction System Description Visualization of Results Discussion Future Work & Conclusion

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

Introduction(Cont.)  One type of information we can use to tame the problems is : People form communities on the Web and reference each other.

System Description  Preprocessing phase The connectivity information is collected  Run-time phase The result are fed into the VANISH tool.

Visualization of Result  “Rick Kazman”

Visualization of Result(Cont.)  “software engineering AND software architecture”

Visualization of Result(Cont.)  “library”

Visualization of Result(Cont.)  “back pain”

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.

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.

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.

Future Work & Conclusion(Cont.)  Replace those visualization techniques with “Core Tree”: How to deal with focus changing? Loop Links