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TiCCo: Time-Centric Content Exploration

Published: 19 October 2020 Publication History

Abstract

Time is a natural way to order information and can be utilized to summarize events and to construct a chronology of contents within a document collection in many application domains. Structuring the sequence of events along a timeline allows users to grasp information at-a-glance, which enables them to get familiar with a topic in only a short amount of time and can hence support the analysis of more complicated and heterogeneous textual data. The manual construction of timelines, however, is a tedious and error-prone task, leading to static timeline representations that limit users to a passive role. In this paper, TiCCo, an automated extraction pipeline from arbitrary English and German text collections, is provided and presented to the user in an interactive manner. This puts the user in an active role in which she not only absorbs knowledge, but also influences in which ways the information is presented to her. In-depth investigations of a specific point in time are augmented by utilizing time-centric co-occurrence graphs that further summarize information extracted from a document collection, and enable users to explore the chronology of events by allowing them to interact with the constructed graphs as well as the underlying documents.

Supplementary Material

MP4 File (3340531.3417432.mp4)
This video showcases TiCCo, a tool for time-centric content exploration. In the video, we present the built framework and outline typical user needs that are approached by TiCCo. The tool divides content into different temporal granularities and then displays a chronology of content within a document collection along a timeline. This timeline representation is complemented by the use of time-centric co-occurrence graphs that summarize the content for any given date. By utilizing this combination, users are enabled to inutively grasp the contents of document collection, since timelines are a well known and established mean to visualize temporal data. We further augment the power of TiCCo by directly linking the nodes and edges of time-centric co-occurrence graphs with the source documents. Hence, users do not need to rely on the contents given in a graph, but can go back to the original documents to verify their assumptions, or to expand their investigation.

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    cover image ACM Conferences
    CIKM '20: Proceedings of the 29th ACM International Conference on Information & Knowledge Management
    October 2020
    3619 pages
    ISBN:9781450368599
    DOI:10.1145/3340531
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    Published: 19 October 2020

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    Author Tags

    1. automatic timeline generation
    2. co-occurrence graph
    3. temporal information
    4. text analytics
    5. text exploration

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