A Study on Optimization of Support Vector Machine Classifier for Word Sense Disambiguation

Lee, Yong-Gu

doi:10.1633/jim.2011.42.2.193

Cited by 2 publications

(2 citation statements)

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“…According to our suggested work, a virtual grid-based dynamic route adjustment and a genetic algorithm will be used to reduce energy consumption while nodes communicate and improve data delivery [11]. Wireless Sensor Network (WSN) applications will benefit from this approach because of its light weight [12,13] and energy-efficient route adjustment processes that are more efficient than those of prior efforts [14,15].…”

Section: Erman Et Al (2012)mentioning

confidence: 99%

Improved Network Validity Using Various Soft Computing Techniques

Yuvaraju¹,

Elakkiyavendan²

2023

Intelligent Automation &Amp; Soft Computing

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Nowadays, when a life span of sensor nodes are threatened by the shortage of energy available for communication, sink mobility is an excellent technique for increasing its lifespan. When communicating via a WSN, the use of nodes as a transmission method eliminates the need for a physical medium. Sink mobility in a dynamic network topology presents a problem for sensor nodes that have reserved resources. Unless the route is revised and changed to reflect the location of the mobile sink location, it will be inefficient for delivering data effectively. In the clustering strategy, nodes are grouped together to improve communication, and the cluster head receives data from compactable nodes. The sink receives the aggregated data from the head. The cluster head is the central node in the conventional technique. A single node uses more energy than a node that is routed to a dead node. Increasing the number of people using a route shortens its lifespan. The proposed work demonstrates the effectiveness with which sensor node paths can be modified at a lower cost by utilising the virtual grid. The best routes are maintained mostly by sink node communication on routes based on dynamic route adjustment (VGDRA). Only specific nodes are acquired to re-align data supply to the mobile sink in accordance with new paradigms of route reconstruction. According to the results, VGDRA schemes have a longer life span because of the reduced number of loops.

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Section: Erman Et Al (2012)mentioning

confidence: 99%

Improved Network Validity Using Various Soft Computing Techniques

Yuvaraju¹,

Elakkiyavendan²

2023

Intelligent Automation &Amp; Soft Computing

View full text Add to dashboard Cite

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“…WSD techniques utilized for the overall corpora are appropriate for this sort of WSD errands. Consequences of applying an existing WSD strategy to the errand of hypernym disambiguation in a monolingual word reference definition [14]. The neural organizations entered the NLP.…”

Section: Introductionmentioning

confidence: 99%

Word Sense Disambiguation Based Sentiment Classification Using Linear Kernel Learning Scheme

Ramya¹,

Karthik²

2023

Intelligent Automation &Amp; Soft Computing

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Word Sense Disambiguation has been a trending topic of research in Natural Language Processing and Machine Learning. Mining core features and performing the text classification still exist as a challenging task. Here the features of the context such as neighboring words like adjective provide the evidence for classification using machine learning approach. This paper presented the text document classification that has wide applications in information retrieval, which uses movie review datasets. Here the document indexing based on controlled vocabulary, adjective, word sense disambiguation, generating hierarchical categorization of web pages, spam detection, topic labeling, web search, document summarization, etc. Here the kernel support vector machine learning algorithm helps to classify the text and feature extract is performed by cuckoo search optimization. Positive review and negative review of movie dataset is presented to get the better classification accuracy. Experimental results focused with context mining, feature analysis and classification. By comparing with the previous work, proposed work designed to achieve the efficient results. Overall design is performed with MATLAB 2020a tool.

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A Study on Optimization of Support Vector Machine Classifier for Word Sense Disambiguation

Cited by 2 publications

References 1 publication

Improved Network Validity Using Various Soft Computing Techniques

Improved Network Validity Using Various Soft Computing Techniques

Word Sense Disambiguation Based Sentiment Classification Using Linear Kernel Learning Scheme

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