SimSumIoT: a platform for simulating the summarisation from Internet of Things

Wei Emma Zhang, Adnan Mahmood, Lixin Deng, Minhao Zhu

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

Abstract

Summarising from the Web could be formed as a problem of multi-document Summarisaiton (MDS) from multiple sources. In contrast to the current MDS problem that involves working on benchmark datasets which provide well clustered set of documents, we envisage to build a pipeline for content Summarisaiton from the Web, but narrow down to the Social Internet of Things (SIoT) paradigm, starting at data collection from the IoT objects, then applying natural language processing techniques for grouping and summarising the data, to distributing summaries back to the IoT objects. In this paper, we present our simulation tool, SimSumIoT, that simulates the process of data sharing, receiving, clustering, and Summarisaiton. A Web-based interface is developed for this purpose allowing users to visualize the process through a set of interactions. The Web interface is accessible via http://simsumlot.tk.

Original languageEnglish
Title of host publicationWSDM '23
Subtitle of host publicationproceedings of the Sixteenth ACM International Conference on Web Search and Data Mining
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Pages1188-1191
Number of pages4
ISBN (Electronic)9781450394079
DOIs
Publication statusPublished - 2023
Event16th ACM International Conference on Web Search and Data Mining, WSDM 2023 - Singapore, Singapore
Duration: 27 Feb 20233 Mar 2023

Conference

Conference16th ACM International Conference on Web Search and Data Mining, WSDM 2023
Country/TerritorySingapore
CitySingapore
Period27/02/233/03/23

Keywords

  • Internet of Things
  • Summarisaiton
  • Natural Language Processing

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