Multi-Modal Media Retrieval via Distance Metric Learning for Potential Customer Discovery

Yang LIU, Zhonglei Gu, Tobey H. Ko, Jiming LIU

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

As social media grown to become an integral part of many people's daily life, brands are quick to launch targeted social media marketing campaign to acquire new potential customers online. To facilitate the potential customer discovery process, a costly and labor intensive manual selection process is done to build a brand portfolio consisting of multimedia data relevant to the brand. To automate this process in a cost-effective way, in this paper, we propose a novel Multi-Modal Distance Metric Learning (M2DML) method, which learns a data-dependent similarity metric from multi-modal media data, aiming at assisting the brands to retrieve appropriate media data from social networks for potential customer discovery. To comprehensively model the supervised information of multi-modal data, M2DML aims to learn both the intra-modality and inter-modality distance metrics simultaneously. To further explore the unsupervised information of the dataset, M2DML aims to preserve the manifold structure of the multi-modal data. The proposed method is then formulated as a standard eigen-decomposition problem and the closed form solution is efficiently computed. Experiments on a standard multi-modal media dataset and a self-collected dataset validate the effectiveness of the proposed method.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages310-317
Number of pages8
ISBN (Electronic)9781538673256
DOIs
Publication statusPublished - 10 Jan 2019
Event18th IEEE/WIC/ACM International Conference on Web Intelligence, WI 2018 - Santiago, Chile
Duration: 3 Dec 20186 Dec 2018

Publication series

NameProceedings - 2018 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2018

Conference

Conference18th IEEE/WIC/ACM International Conference on Web Intelligence, WI 2018
Country/TerritoryChile
CitySantiago
Period3/12/186/12/18

Scopus Subject Areas

  • Artificial Intelligence
  • Computer Networks and Communications

User-Defined Keywords

  • Multi-modal distance metric learning
  • Multi-modal media retrieval
  • Potential customer discovery
  • Social media mining

Fingerprint

Dive into the research topics of 'Multi-Modal Media Retrieval via Distance Metric Learning for Potential Customer Discovery'. Together they form a unique fingerprint.

Cite this