LogCanvas: Visualizing Search History Using Knowledge Graphs
Luyan Xu, Zeon Trevor Fernando, Xuan Zhou, Wolfgang Nejdl

TL;DR
LogCanvas is a visualization platform that reconstructs users' search history as knowledge graphs, highlighting semantic relationships and enabling efficient re-finding of information through session timelines and collaborative sharing.
Contribution
It introduces a novel visualization tool that represents search history as knowledge graphs, emphasizing semantic relationships and collaborative features.
Findings
Effective visualization of search sessions as knowledge graphs.
Enhanced ability to re-find previous search results.
Support for collaborative sharing of search experiences.
Abstract
In this demo paper, we introduce LogCanvas, a platform for user search history visualisation. Different from the existing visualisation tools, LogCanvas focuses on helping users re-construct the semantic relationship among their search activities. LogCanvas segments a user's search history into different sessions and generates a knowledge graph to represent the information exploration process in each session. A knowledge graph is composed of the most important concepts or entities discovered by each search query as well as their relationships. It thus captures the semantic relationship among the queries. LogCanvas offers a session timeline viewer and a snippets viewer to enable users to re-find their previous search results efficiently. LogCanvas also provides a collaborative perspective to support a group of users in sharing search results and experience.
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