Column networks for collective classification

Trang Pham, Truyen Tran, Dinh Phung, Svetha Venkatesh

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

95 Citations (Scopus)


Relational learning deals with data that are characterized by relational structures. An important task is collective classification, which is to jointly classify networked objects. While it holds a great promise to produce a better accuracy than non-collective classifiers, collective classification is computationally challenging and has not leveraged on the recent breakthroughs of deep learning. We present Column Network (CLN), a novel deep learning model for collective classification in multi-relational domains. CLN has many desirable theoretical properties: (i) it encodes multi-relations between any two instances; (ii) it is deep and compact, allowing complex functions to be approximated at the network level with a small set of free parameters; (iii) local and relational features are learned simultaneously; (iv) long-range, higher-order dependencies between instances are supported naturally; and (v) crucially, learning and inference are efficient with linear complexity in the size of the network and the number of relations. We evaluate CLN on multiple real-world applications: (a) delay prediction in software projects, (b) PubMed Diabetes publication classification and (c) film genre classification. In all of these applications, CLN demonstrates a higher accuracy than state-of-the-art rivals.

Original languageEnglish
Title of host publicationProceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17)
Subtitle of host publicationFebruary 4-9, 2017 Hilton San Francisco Union Square San Francisco, California, USA
EditorsSatinder Singh, Shaul Markovitch
Place of PublicationPalo Alto CA USA
PublisherAssociation for the Advancement of Artificial Intelligence (AAAI)
Number of pages7
Publication statusPublished - 2017
Externally publishedYes
EventAAAI Conference on Artificial Intelligence 2017 - Hilton San Francisco Union Square, San Francisco, United States of America
Duration: 4 Feb 201710 Feb 2017
Conference number: 31st


ConferenceAAAI Conference on Artificial Intelligence 2017
Abbreviated titleAAAI 2017
Country/TerritoryUnited States of America
CitySan Francisco
Internet address

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