{"id":308,"date":"2014-05-17T00:12:15","date_gmt":"2014-05-17T00:12:15","guid":{"rendered":"https:\/\/staff.fnwi.uva.nl\/m.derijke\/?p=308"},"modified":"2015-05-03T15:27:14","modified_gmt":"2015-05-03T15:27:14","slug":"sigir-2014-paper-on-hierarchical-multi-label-classification-of-social-text-streams-online","status":"publish","type":"post","link":"https:\/\/staff.fnwi.uva.nl\/m.derijke\/sigir-2014-paper-on-hierarchical-multi-label-classification-of-social-text-streams-online\/","title":{"rendered":"SIGIR 2014 paper on hierarchical multi-label classification of social text streams online"},"content":{"rendered":"<p>Our SIGIR 2014 paper on \u201cHierarchical multipliable classification of social text streams\u201c by Zhaochun Ren, Maria-Hendrike Peetz, Shangsong Liang, Willemijn van Dolen and Maarten de Rijke is\u00a0<a href=\"http:\/\/staff.fnwi.uva.nl\/m.derijke\/content\/publications\/sigir2014-fp-classification.pdf\" rel=\"self\">available<\/a>\u00a0online now.<\/p>\n<p>Hierarchical multi-label classification assigns a document to multiple hierarchical classes. In this paper we focus on hierarchical multi-label classification of social text streams. Concept drift, complicated relations among classes, and the limited length of documents in social text streams make this a challenging problem. Our approach includes three core ingredients: short document expansion, time-aware topic tracking, and chunk-based structural learning. We extend each short document in social text streams to a more comprehensive representation via state-of-the-art entity linking and sentence ranking strategies. From documents extended in this manner, we infer dynamic probabilistic distributions over topics by dividing topics into dynamic &#8220;global&#8221; topics and &#8220;local&#8221; topics. For the third and final phase we propose a chunk-based structural optimization strategy to classify each document into multiple classes. Extensive experiments conducted on a large real-world dataset show the effectiveness of our proposed method for hierarchical multi-label classification of social text streams.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Our SIGIR 2014 paper on \u201cHierarchical multipliable classification of social text streams\u201c by Zhaochun Ren, Maria-Hendrike Peetz, Shangsong Liang, Willemijn van Dolen and Maarten de Rijke is\u00a0available\u00a0online now. Hierarchical multi-label classification assigns a document to multiple hierarchical classes. In this paper we focus on hierarchical multi-label classification of social text streams. Concept drift, complicated relations&#8230;<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[],"_links":{"self":[{"href":"https:\/\/staff.fnwi.uva.nl\/m.derijke\/wp-json\/wp\/v2\/posts\/308"}],"collection":[{"href":"https:\/\/staff.fnwi.uva.nl\/m.derijke\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/staff.fnwi.uva.nl\/m.derijke\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/staff.fnwi.uva.nl\/m.derijke\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/staff.fnwi.uva.nl\/m.derijke\/wp-json\/wp\/v2\/comments?post=308"}],"version-history":[{"count":1,"href":"https:\/\/staff.fnwi.uva.nl\/m.derijke\/wp-json\/wp\/v2\/posts\/308\/revisions"}],"predecessor-version":[{"id":309,"href":"https:\/\/staff.fnwi.uva.nl\/m.derijke\/wp-json\/wp\/v2\/posts\/308\/revisions\/309"}],"wp:attachment":[{"href":"https:\/\/staff.fnwi.uva.nl\/m.derijke\/wp-json\/wp\/v2\/media?parent=308"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/staff.fnwi.uva.nl\/m.derijke\/wp-json\/wp\/v2\/categories?post=308"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/staff.fnwi.uva.nl\/m.derijke\/wp-json\/wp\/v2\/tags?post=308"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}