loading
Documents

Research.Publish.Connect.

Paper

Authors: Antonio M. Rinaldi 1 and Cristiano Russo 2

Affiliations: 1 Dipartimento di Ingegneria Elettrica e delle Tecnologie dell’Informazione, IKNOS-LAB-Intelligent and Knowledge Systems-LUPT, University of Naples Federico II and Italy ; 2 LISSI Laboratory, University of Paris-Est Creteil (UPEC) and France

ISBN: 978-989-758-330-8

Keyword(s): Document Representation, Semantic and Linguistic Analysis, WordNet, Lexical Chains, NoSQL, Neo4J.

Abstract: As an increasing number of text-based documents, whose complexity increases in turn, are available over the Internet, it becomes obvious that handling such documents as they are, i.e. in their original natural-language based format, represents a daunting task to face up for computers. Thus, some methods and techniques have been used and refined, throughout the last decades, in order to transform the digital documents from the full text version to another suitable representation, making them easier to handle and thus helping users in getting the right information with a reduced algorithmic complexity. One of the most spread solution in document representation and retrieval has consisted in transforming the full text version into a vector, which describes the contents of the document in terms of occurrences patterns of words. Although the wide adoption of this technique, some remarkable drawbacks have been soon pointed out from the researchers’ community, mainly focused on the lack of s emantics for the associated terms. In this work, we use WordNet as a generalist linguistic database in order to enrich, at a semantic level, the document representation by exploiting a label and properties based graph model, implemented in Neo4J. This work demonstrates how such representation allows users to quickly recognize the document topics and lays the foundations for cross-document relatedness measures that go beyond the mere word-centric approach. (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 54.81.220.239

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:
Rinaldi, A. and Russo, C. (2018). A Novel Framework to Represent Documents using a Semantically-grounded Graph Model.In Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, ISBN 978-989-758-330-8, pages 203-211. DOI: 10.5220/0006932502030211

@conference{kdir18,
author={Antonio M. Rinaldi. and Cristiano Russo.},
title={A Novel Framework to Represent Documents using a Semantically-grounded Graph Model},
booktitle={Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR,},
year={2018},
pages={203-211},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006932502030211},
isbn={978-989-758-330-8},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR,
TI - A Novel Framework to Represent Documents using a Semantically-grounded Graph Model
SN - 978-989-758-330-8
AU - Rinaldi, A.
AU - Russo, C.
PY - 2018
SP - 203
EP - 211
DO - 10.5220/0006932502030211

Login or register to post comments.

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