Linkify: Enhancing Text Reading Experience by Detecting and Linking Helpful Entities to Users

Ikuya Yamada, Tomotaka Ito, Hideaki Takeda, Yoshiyasu Takefuji

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

We frequently encounter unfamiliar entity names (e.g., a person's name or a geographic location) while reading texts such as newspapers, magazines, and web pages. When this occurs, we typically perform a sequence of tedious actions: select the entity name, submit it to a search engine, and obtain detailed information from websites. In this paper, we present Linkify, a tool that enhances text reading by automatically converting entity names into links and displaying a widget that contains links to several relevant websites. We also propose a novel method for evaluating the helpfulness of entities to users using supervised machine learning with a set of carefully designed features. Experimental results show that our method significantly outperforms existing state-of-the-art methods.

Original languageEnglish
Article number8255781
Pages (from-to)37-46
Number of pages10
JournalIEEE Intelligent Systems
Volume33
Issue number5
DOIs
Publication statusPublished - 2018 Sep 1

Keywords

  • artificial intelligence
  • computing methodologies
  • hypertext/hypermedia
  • information interfaces and representation (hci)
  • information technology and systems
  • intelligent web services and semantic web
  • natural language processing
  • text analysis
  • web text analysis

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Artificial Intelligence

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