{"id":4066,"date":"2020-05-04T19:16:14","date_gmt":"2020-05-04T19:16:14","guid":{"rendered":"https:\/\/ailab.ijs.si\/?page_id=4066"},"modified":"2021-04-19T22:18:52","modified_gmt":"2021-04-19T22:18:52","slug":"highlights-in-2016","status":"publish","type":"page","link":"https:\/\/ailab.ijs.si\/si\/publications\/highlights\/highlights-in-2016\/","title":{"rendered":"Highlights in 2016"},"content":{"rendered":"<table width=\"568\">\n<tbody>\n<tr>\n<td width=\"20\">1<\/td>\n<td width=\"420\"><strong>KARLOV\u010cEC, Mario<\/strong>, LU\u017dAR, Borut, <strong>MLADENI\u0106, Dunja<\/strong>. Core-periphery dynamics in collaboration networks: the case study of Slovenia. Scientometrics, December 2016, Volume 109, Issue 3, pp 1561\u20131578<\/td>\n<\/tr>\n<tr>\n<td>2<\/td>\n<td width=\"462\"><strong>TOMA\u0160EV, Nenad<\/strong>, BUZA, Krisztian, <strong>MLADENI\u0106, Dunja<\/strong>. Correcting the hub occurrence prediction bias in many dimensions. Computer science and information systems, 2016, vol. 13, no. 1, pp 1-21 [<a href=\"https:\/\/ailab.ijs.si\/wp-content\/uploads\/2020\/05\/Correcting-the-hub-occurrence-prediction-bias-in-many-dimensions.pdf\">pdf<\/a>]<\/td>\n<\/tr>\n<tr>\n<td>3<\/td>\n<td width=\"462\"><strong>\u0160KRABA, Primo\u017e<\/strong>, ROSEN, Paul, WANG, Bei, CHEN, Guoning, BHATIA, Harsh, PASCUCCI, Valerio. Critical point cancellation in 3D vector fields. IEEE transactions on visualization and computer graphics, 2016, vol. 22, no. 6, pp 1683-1693 [<a href=\"http:\/\/www.sci.utah.edu\/~beiwang\/publications\/3D_VF_Robustness_BeiWang_2016.pdf\">pdf<\/a>]<\/td>\n<\/tr>\n<tr>\n<td>4<\/td>\n<td width=\"462\"><strong>RUPNIK, Jan<\/strong>, <strong>MUHI\u010c, Andrej<\/strong>, <strong>LEBAN, Gregor<\/strong>, <strong>\u0160KRABA, Primo\u017e<\/strong>, <strong>FORTUNA, Bla\u017e<\/strong>, <strong>GROBELNIK, Marko<\/strong>. News across languages - cross-lingual document similarity and event tracking. The journal of artificial intelligence research, 2016, vol. 55, pp 283-316 [<a href=\"https:\/\/ailab.ijs.si\/wp-content\/uploads\/2020\/05\/News-across-languages-\u2013-cross-lingual-document-similarity-and-event-tracking.pdf\">pdf<\/a>]<\/td>\n<\/tr>\n<tr>\n<td>5<\/td>\n<td width=\"462\"><strong>KUDRYAVTSEVA, Ganna<\/strong>, <strong>\u0160KRABA, Primo\u017e<\/strong>. The principal bundles over an inverse semigroup. Semigroup forum, 2016, 22 pp [<a href=\"https:\/\/ailab.ijs.si\/wp-content\/uploads\/2020\/05\/The-principal-bundles-over-an-inverse-semigroup.pdf\">pdf<\/a>]<\/td>\n<\/tr>\n<tr>\n<td>6<\/td>\n<td width=\"462\">FORTUNA, Carolina, DE POORTER, Eli, <strong>\u0160KRABA, Primo\u017e<\/strong>, MOERMAN, Ingrid. Data driven wireless network design : a multi-level modeling approach. Wireless personal communications, [in press] 2016, 15 pp [<a href=\"https:\/\/ailab.ijs.si\/wp-content\/uploads\/2020\/05\/Data-driven-wireless-network-design-A-multi-level-modeling-approach.pdf\">pdf<\/a>]<\/td>\n<\/tr>\n<tr>\n<td>7<\/td>\n<td width=\"462\"><strong>GROBELNIK, Marko<\/strong>, <strong>MLADENI\u0106, Dunja<\/strong>, WITBROCK, Michael J. Text mining for the semantic web. V: SAMMUT, Claude (ur.), WEBB, Geoffrey I. (ur.). Encyclopedia of machine learning and data mining. Heidelberg [etc.]: Springer, 2016, 3 pages<\/td>\n<\/tr>\n<tr>\n<td>8<\/td>\n<td width=\"462\"><strong>MLADENI\u0106, Dunja<\/strong>, <strong>BRANK, Janez<\/strong>, <strong>GROBELNIK, Marko<\/strong>. Document classification. In: SAMMUT, Claude, WEBB, Geoffrey I. (eds.). Encyclopedia of machine learning and data mining. Heidelberg [etc.]: Springer, 2016, 5 pages<\/td>\n<\/tr>\n<tr>\n<td>9<\/td>\n<td width=\"462\"><strong>BRANK, Janez<\/strong>, <strong>MLADENI\u0106, Dunja<\/strong>, <strong>GROBELNIK, Marko<\/strong>. Feature construction in text mining. V: SAMMUT, Claude (ur.), WEBB, Geoffrey I. (ur.). Encyclopedia of machine learning and data mining. Heidelberg [etc.]: Springer, 2016, 6 pages<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n","protected":false},"excerpt":{"rendered":"<p>1 KARLOV\u010cEC, Mario, LU\u017dAR, Borut, MLADENI\u0106, Dunja. Core-periphery dynamics in collaboration networks: the case study of Slovenia. Scientometrics, December 2016, Volume 109, Issue 3, pp 1561\u20131578 2 TOMA\u0160EV, Nenad, BUZA, Krisztian, MLADENI\u0106, Dunja. Correcting the hub occurrence prediction bias in many dimensions. Computer science and information systems, 2016, vol. 13, no. 1, pp 1-21 [pdf] [&hellip;]<\/p>\n","protected":false},"author":42,"featured_media":0,"parent":4080,"menu_order":3,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-4066","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/ailab.ijs.si\/si\/wp-json\/wp\/v2\/pages\/4066","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ailab.ijs.si\/si\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/ailab.ijs.si\/si\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/ailab.ijs.si\/si\/wp-json\/wp\/v2\/users\/42"}],"replies":[{"embeddable":true,"href":"https:\/\/ailab.ijs.si\/si\/wp-json\/wp\/v2\/comments?post=4066"}],"version-history":[{"count":5,"href":"https:\/\/ailab.ijs.si\/si\/wp-json\/wp\/v2\/pages\/4066\/revisions"}],"predecessor-version":[{"id":4204,"href":"https:\/\/ailab.ijs.si\/si\/wp-json\/wp\/v2\/pages\/4066\/revisions\/4204"}],"up":[{"embeddable":true,"href":"https:\/\/ailab.ijs.si\/si\/wp-json\/wp\/v2\/pages\/4080"}],"wp:attachment":[{"href":"https:\/\/ailab.ijs.si\/si\/wp-json\/wp\/v2\/media?parent=4066"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}