loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Anshuman Saxena 1 ; Ashish Bindal 2 and Alain Wegmann 2

Affiliations: 1 I&C EPFL and TCS Innovation Labs, Switzerland ; 2 I&C EPFL, Switzerland

ISBN: 978-989-8565-75-4

Keyword(s): Service Design, Part-whole Relations, Situated Conceptualization, Linguistic Markers, Digraph Analysis.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Business Intelligence Applications ; Concept Mining ; Information Extraction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Symbolic Systems

Abstract: A compositional hierarchy is the default organization of knowledge acquired for the purpose of specifying the design requirements of a service. Existing methods for learning compositional hierarchies from natural language text, interpret composition as an exclusively propositional form of part-whole relations. Nevertheless, the lexico-syntactic patterns used to identify the occurrence of part-whole relations fail to decode the experientially grounded information, which is very often embedded in various acts of natural language expression, e.g. construction and delivery. The basic idea is to take a situated view of conceptualization and model composition as the cognitive act of invoking one category to refer to another. Mutually interdependent set of categories are considered conceptually inseparable and assigned an independent level of abstraction in the hierarchy. Presence of such levels in the compositional hierarchy highlight the need to model these categories as a unified-whole wh erein they can only be characterized in the context of the behavior of the set as a whole. We adopt an object-oriented representation approach that models categories as entities and relations as cognitive references inferred from syntactic dependencies. The resulting digraph is then analyzed for cyclic references, which are resolved by introducing an additional level of abstraction for each cycle. (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 18.234.51.17

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:
Saxena, A.; Bindal, A. and Wegmann, A. (2013). A Cognitive Reference based Model for Learning Compositional Hierarchies with Whole-composite Tags.In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013) ISBN 978-989-8565-75-4, pages 119-127. DOI: 10.5220/0004542201190127

@conference{kdir13,
author={Anshuman Saxena. and Ashish Bindal. and Alain Wegmann.},
title={A Cognitive Reference based Model for Learning Compositional Hierarchies with Whole-composite Tags},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013)},
year={2013},
pages={119-127},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004542201190127},
isbn={978-989-8565-75-4},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013)
TI - A Cognitive Reference based Model for Learning Compositional Hierarchies with Whole-composite Tags
SN - 978-989-8565-75-4
AU - Saxena, A.
AU - Bindal, A.
AU - Wegmann, A.
PY - 2013
SP - 119
EP - 127
DO - 10.5220/0004542201190127

Login or register to post comments.

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