Discovering Latent Information By Spreading Activation Algorithm for Document Retrieval

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Title: Discovering Latent Information By Spreading Activation Algorithm for Document Retrieval
Authors: Ngo, Vuong M.
Permanent link: http://hdl.handle.net/10197/11807
Date: 31-Jan-2014
Online since: 2020-12-11T10:52:38Z
Abstract: Syntactic search relies on keywords contained in a query to find suitable documents. So, documents that do not contain the keywords but contain information related to the query are not retrieved. Spreading activation is an algorithm for finding latent information in a query by exploiting relations between nodes in an associative network or semantic network. However, the classical spreading activation algorithm uses all relations of a node in the network that will add unsuitable information into the query. In this paper, we propose a novel approach for semantic text search, called query-oriented-constrained spreading activation that only uses relations relating to the content of the query to find really related information. Experiments on a benchmark dataset show that, in terms of the MAP measure, our search engine is 18.9% and 43.8% respectively better than the syntactic search and the search using the classical constrained spreading activation
Type of material: Journal Article
Publisher: Academy and Industry Research Collaboration Center
Journal: International Journal of Artificial Intelligence & Applications
Volume: 5
Issue: 1
Start page: 23
End page: 34
Keywords: Information retrievalOntologySemantic searchSpreading activation
DOI: 10.5121/ijaia.2014.5102
Other versions: http://airccse.org/journal/ijaia/current2014.html
Language: en
Status of Item: Peer reviewed
ISSN: 0976-2191
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Computer Science Research Collection

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