loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: André Gohr 1 ; Myra Spiliopoulou 2 and Alexander Hinneburg 3

Affiliations: 1 Leibniz Institute of Plant Biochemistry, Germany ; 2 Otto-von-Guericke University, Germany ; 3 Martin-Luther University Halle-Wittenberg, Germany

ISBN: 978-989-8425-28-7

Keyword(s): Knowledge management, Visualization, Social web, Tag semantics, Topic modeling.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Business Analytics ; Data Analytics ; Data Engineering ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Mining High-Dimensional Data ; Mining Text and Semi-Structured Data ; Symbolic Systems ; Visual Data Mining and Data Visualization

Abstract: Tags are intensively used in social platforms to annotate resources: Tagging is a social phenomenon, because users do not only annotate to organize their resources but also to associate semantics to resources contributed by third parties. This leads often to semantic ambiguities: Popular tags are associated with very disparate meanings, even to the extend that some tags (e.g. ”beautiful” or ”toread”) are irrelevant to the semantics of the resources they annotate. We propose a method that learns a topic model for documents under a tag and visualizes the different meanings associated with the tag. Our approach deals with the following problems. First, tag miscellany is a temporal phenomenon: tags acquire multiple semantics gradually, as users apply them to disparate documents. Hence, our method must capture and visualize the evolution of the topics in a stream of documents. Second, the meanings associated to a tag must be presented in a human-understandable way; This concerns both the c hoice of words and the visualization of all meanings. Our method uses AdaptivePLSA, a variation of Probabilistic Latent Semantic Analysis for streams, to learn and adapt topics on a stream of documents annotated with a specific tag. We propose a visualization technique called Topic Table to visualize document prototypes derived from topics and their evolution over time. We show by a case study how our method captures the evolution of tags selected as frequent and ambiguous, and visualizes their semantics in a comprehensible way. Additionally, we show the effectiveness by adding alien resources under a tag. Our approach indeed visualizes hints to the added documents. (More)

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 54.92.193.89

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Gohr A., Spiliopoulou M. and Hinneburg A. (2010). VISUALLY SUMMARIZING THE EVOLUTION OF DOCUMENTS UNDER A SOCIAL TAG.In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010) ISBN 978-989-8425-28-7, pages 85-94. DOI: 10.5220/0003096100850094

@conference{kdir10,
author={André Gohr and Myra Spiliopoulou and Alexander Hinneburg},
title={VISUALLY SUMMARIZING THE EVOLUTION OF DOCUMENTS UNDER A SOCIAL TAG},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010)},
year={2010},
pages={85-94},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003096100850094},
isbn={978-989-8425-28-7},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010)
TI - VISUALLY SUMMARIZING THE EVOLUTION OF DOCUMENTS UNDER A SOCIAL TAG
SN - 978-989-8425-28-7
AU - Gohr A.
AU - Spiliopoulou M.
AU - Hinneburg A.
PY - 2010
SP - 85
EP - 94
DO - 10.5220/0003096100850094

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.