Enrichment of academic search engine results pages by citation-based graphs

Shuhei Shogen, Toshiyuki Shimizu, Masatoshi Yoshikawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)


Researchers’ readings of academic papers make their research more sophisticated and objective. In this paper, we describe a method of supporting scholarly surveys by incorporating a graph based on citation relationships into the results page of an academic search engine. Conventional academic search engines have a problem in that users have difficulty in determining which academic papers are relevant to their needs because it is hard to understand the relationship between the academic papers that appear in the search results pages. Our method helps users to make judgments about the relevance of papers by clearly visualizing the relationship. It visualizes not only academic papers on the results page but also papers that have a strong citation relationship with them. We carefully considered the method of visualization and implemented a prototype with which we conducted a user study simulating scholarly surveys. We confirmed that our method improved the efficiency of scholarly surveys through the user study.

Original languageEnglish
Title of host publicationInformation Retrieval Technology - 11th Asia Information Retrieval Societies Conference, AIRS 2015, Proceedings
EditorsFalk Scholer, Guido Zuccon, Shlomo Geva, Aixin Sun, Hideo Joho, Peng Zhang
PublisherSpringer Verlag
Number of pages12
ISBN (Print)9783319289397
Publication statusPublished - 2015
Externally publishedYes
Event11th Asia Information Retrieval Societies Conference, AIRS 2015 - Brisbane, Australia
Duration: Dec 2 2015Dec 4 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th Asia Information Retrieval Societies Conference, AIRS 2015

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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