Abstract | ||
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Attribute-based naming enables powerful search and organization tools for ever-increasing user data sets. However, such tools are only useful in combination with accurate attribute assignment. Existing systems rely on user input and content analysis, but they have enjoyed minimal success. This paper discusses new approaches to automatically assigning attributes to files, including several forms of context analysis, which has been highly successful in the Google web search engine. With extensions like application hints (e.g., web links for downloaded files) and inter-file relationships, it should be possible to infer useful attributes for many files, making attribute-based search tools more effective. |
Year | Venue | Keywords |
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2003 | HotOS | google web search engine,attribute-based naming,useful attribute,user input,content analysis,powerful search,new method,attribute-based search tool,web link,ever-increasing user data set,context analysis,attribute assignment,web search engine |
Field | DocType | Citations |
Web search engine,Content analysis,World Wide Web,Data set,Context analysis,Computer science | Conference | 14 |
PageRank | References | Authors |
0.88 | 13 | 2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Craig A. N. Soules | 1 | 591 | 45.41 |
Gregory R. Ganger | 2 | 4560 | 383.16 |