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Intelligent Information Retrieval Technique for Wireless Sensor Networks

Published: 10 August 2015 Publication History

Abstract

Wireless Sensor Networks play a vital role in military applications. In Military it's very important to extract the actual information from the transmitted message. Sentiment analysis is a valuable knowledge resource which analyses collective sentiments of a text and helps in decision making. This paper proposes an Intelligent Information Retrieval Technique (IIRT) based on SentiWordNet, a lexical resource which is used for aspect analysis of text messages sent among military groups. The Proposed IIRT extracts the intelligent information from the text messages transmitted in military groups in WSNs. Proposed IIRT is based on sentiment analysis, where first the aggregated message is filtered then segregated with the help of lemmatization and then opinion words are gathered by grammatical tagging. At last aspect analysis of these opinion words is done with the help of SentiWordNet. IIRT gathers the intelligent information from the original message by calculating the polarity values of the opinion words. The proposed IIRT is executed on the time stamping data messages sent among military groups in wireless sensor networks and the results prove the correctness and accuracy of our IIRT.

References

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Bhaskar, J., K., S. and Nedungadi, P. 2014. Enhanced Sentiment Analysis of Informal Textual Communication in Social Media by Considering Objective Words and Intensifiers. IEEE International Conference on Recent Advances and Innovations in Engineering (Jaipur, India, May 09-14 2014). ICRAIE'14, 1--6.
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Chinsha, T.C., Joseph, S. 2015. A Syntactic Approach for Aspect Based Opinion Mining. In Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (Anaheim, California, Feb 7-9 2015). ICSC'15, 24--31.
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Singh, V.K., Piryani, R., Uddin, A. and Walia, P. 2013. Sentiment Analysis of Movie Reviews and Blog Posts. 3rd IEEE International Advance Computing Conference (Ghaziabad, India Feb 22-23 2013). IACCF'13, 893--898.
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Hamouda, A., Rohaim, M. 2011. Reviews Classification using SentiWordNet Lexicon. The Online Journal on Computer Science and Information Technology, 2, 1 (2011), 120--123.
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SentiWordNet available at sentiwordnet.isti.cnr.it/
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Benamara, F., Cesarano, C. and Reforigiato, D. 2007. Sentiment Analysis: Adjectives, Adverbs are better than Adjectives alone. Proceedings of ICWSM (Boulder, CO, USA, March 26-28 2007). ICWSM'07, 1--7.
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Cited By

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  • (2016)Intelligent information retrieval in a Tsunami detection system using wireless sensor networks2016 International Conference on Computing, Communication and Automation (ICCCA)10.1109/CCAA.2016.7813873(939-944)Online publication date: Apr-2016
  • (2015)Deployment of Wireless Sensor Networks for intelligent information retrieval in marine environment2015 IEEE International Conference on Control System, Computing and Engineering (ICCSCE)10.1109/ICCSCE.2015.7482214(371-376)Online publication date: Nov-2015

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cover image ACM Other conferences
WCI '15: Proceedings of the Third International Symposium on Women in Computing and Informatics
August 2015
763 pages
ISBN:9781450333610
DOI:10.1145/2791405
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 10 August 2015

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Author Tags

  1. Intelligent Data
  2. Opinion Mining
  3. SentiWordNet
  4. Sentiment Analysis
  5. Wireless Sensor Networks

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WCI '15

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WCI '15 Paper Acceptance Rate 98 of 452 submissions, 22%;
Overall Acceptance Rate 98 of 452 submissions, 22%

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View all
  • (2016)Intelligent information retrieval in a Tsunami detection system using wireless sensor networks2016 International Conference on Computing, Communication and Automation (ICCCA)10.1109/CCAA.2016.7813873(939-944)Online publication date: Apr-2016
  • (2015)Deployment of Wireless Sensor Networks for intelligent information retrieval in marine environment2015 IEEE International Conference on Control System, Computing and Engineering (ICCSCE)10.1109/ICCSCE.2015.7482214(371-376)Online publication date: Nov-2015

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