LogCanvas: Visualizing Search History Using Knowledge Graphs

August 15, 2018 Β· Declared Dead Β· πŸ› Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

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Authors Luyan Xu, Zeon Trevor Fernando, Xuan Zhou, Wolfgang Nejdl arXiv ID 1808.05127 Category cs.HC: Human-Computer Interaction Cross-listed cs.SI Citations 16 Venue Annual International ACM SIGIR Conference on Research and Development in Information Retrieval Last Checked 3 months ago
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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