{"id":5610,"date":"2011-09-19T15:47:08","date_gmt":"2011-09-19T12:47:08","guid":{"rendered":"http:\/\/hgpu.org\/?p=5610"},"modified":"2011-09-19T15:47:08","modified_gmt":"2011-09-19T12:47:08","slug":"a-small-world-network-model-for-distributed-storage-of-semantic-metadata","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=5610","title":{"rendered":"A small-world network model for distributed storage of semantic metadata"},"content":{"rendered":"<p>The growing uptake of semantic web and grid ideas is raising the importance of optimising distribution algorithms for semantic metadata. While it is not yet clear how real-world metadata distribution patterns ought to evolve, practical experience of social and technical networks suggests that a small-world pattern is desirable and practical. We explore simulated small-world networks of semantic metadata and some graph parameters and metrics. We discuss the implications of inter- and intra-domain path lengths for semantic queries on web and grid structures.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The growing uptake of semantic web and grid ideas is raising the importance of optimising distribution algorithms for semantic metadata. While it is not yet clear how real-world metadata distribution patterns ought to evolve, practical experience of social and technical networks suggests that a small-world pattern is desirable and practical. We explore simulated small-world networks [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[11,89,3],"tags":[117,1782,14,948,20],"class_list":["post-5610","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-paper","tag-artificial-intelligence","tag-computer-science","tag-cuda","tag-networks","tag-nvidia"],"views":1943,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5610","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=5610"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5610\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5610"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5610"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5610"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}