Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
Article Fingerprint
ReserarchID
CSTSDE5S89Q
Information Retrieval in a Telugu language is upcoming area of research. Telugu is one of the recognized Indian languages. We present a novel approach in reformulating item terms at the time of crawling and indexing. The idea is not new, but use of synset and other lexical resources in Indian languages context has limitations due to unavailability of language resources. We prepared a synset for 1,43,001 root words out of 4,83,670 unique words from training corpus of 3500 documents during indexing. Index time document expansion gave improved recall ratio, when compared to base line approach i.e. simple information retrieval without term expansion at both the ends. We studied the effect of query terms expansion at search time using synset and compared with simple information retrieval process without expansion, recall is greatly affected and improved. We further extended this work by expanding terms in two sides and plotted results, which resemble recall growth. Surprisingly all expansions are showing improvement in recall and little fall in precision. We argue that expansion of terms at any level may cause inverse effect on precision. Necessary care is required while expanding documents or queries with help of language resources like Synset, WordNet and other resources.
Ramakrishna kolikipogu. 2013. \u201cDynamic Vs Static Term-Expansion using Semantic Resources in Information Retrieval\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 13 (GJCST Volume 13 Issue C4): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
The methods for personal identification and authentication are no exception.
Total Score: 102
Country: Unknown
Subject: Global Journal of Computer Science and Technology - C: Software & Data Engineering
Authors: Ramakrishna kolikipogu, Padmaja Rani B (PhD/Dr. count: 0)
View Count (all-time): 228
Total Views (Real + Logic): 9356
Total Downloads (simulated): 2477
Publish Date: 2013 05, Thu
Monthly Totals (Real + Logic):
Neural Networks and Rules-based Systems used to Find Rational and
A Comparative Study of the Effeect of Promotion on Employee
The Problem Managing Bicycling Mobility in Latin American Cities: Ciclovias
Impact of Capillarity-Induced Rising Damp on the Energy Performance of
Information Retrieval in a Telugu language is upcoming area of research. Telugu is one of the recognized Indian languages. We present a novel approach in reformulating item terms at the time of crawling and indexing. The idea is not new, but use of synset and other lexical resources in Indian languages context has limitations due to unavailability of language resources. We prepared a synset for 1,43,001 root words out of 4,83,670 unique words from training corpus of 3500 documents during indexing. Index time document expansion gave improved recall ratio, when compared to base line approach i.e. simple information retrieval without term expansion at both the ends. We studied the effect of query terms expansion at search time using synset and compared with simple information retrieval process without expansion, recall is greatly affected and improved. We further extended this work by expanding terms in two sides and plotted results, which resemble recall growth. Surprisingly all expansions are showing improvement in recall and little fall in precision. We argue that expansion of terms at any level may cause inverse effect on precision. Necessary care is required while expanding documents or queries with help of language resources like Synset, WordNet and other resources.
We are currently updating this article page for a better experience.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.