Embedding-based representation of categorical data by hierarchical value coupling learning

Songlei Jian, Longbing Cao, Guansong Pang, Kai Lu, Hang Gao

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

29 Citations (Scopus)

Abstract

Learning the representation of categorical data with hierarchical value coupling relationships is very challenging but critical for the effective analysis and learning of such data. This paper proposes a novel coupled unsupervised categorical data representation (CURE) framework and its instantiation, i.e., a coupled data embedding (CDE) method, for representing categorical data by hierarchical valueto-value cluster coupling learning. Unlike existing embedding- and similarity-based representation methods which can capture only a part or none of these complex couplings, CDE explicitly incorporates the hierarchical couplings into its embedding representation. CDE first learns two complementary feature value couplings which are then used to cluster values with different granularities. It further models the couplings in value clusters within the same granularity and with different granularities to embed feature values into a new numerical space with independent dimensions. Substantial experiments show that CDE significantly outperforms three popular unsupervised embedding methods and three state-of-the-art similarity-based representation methods.

Original languageEnglish
Title of host publicationProceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence
EditorsCarles Sierra
Place of PublicationCalifornia
PublisherInternational Joint Conferences on Artificial Intelligence
Pages1937-1943
Number of pages7
ISBN (Electronic)9780999241103
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event26th International Joint Conference on Artificial Intelligence, IJCAI 2017 - Melbourne, Australia
Duration: 19 Aug 201725 Aug 2017

Conference

Conference26th International Joint Conference on Artificial Intelligence, IJCAI 2017
Country/TerritoryAustralia
CityMelbourne
Period19/08/1725/08/17

Fingerprint

Dive into the research topics of 'Embedding-based representation of categorical data by hierarchical value coupling learning'. Together they form a unique fingerprint.

Cite this