Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Cluster Computing
Published in: Cluster Computing 3/2019

23-02-2018

Intelligent sentence retrieval using semantic word based answer generation algorithm with cuckoo search optimization

Authors: Karpagam Kanagarajan, Saradha Arumugam

Published in: Cluster Computing | Special Issue 3/2019

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

The question answering system is a major area in information retrieval field to get the appropriate answers to the user query instead of list of documents. Nowadays huge amount of documents uploaded in the Internet every day and the extraction of required information from those documents is a challenging and tedious task. In this paper, POS-tagger based question pattern analysis has applied for recognize the question type. Also introduce the semantic words based answer generator algorithm to extract semantic similar sentences for user query using Wordnet from the knowledgebase. The cuckoo search optimization algorithm has applied with the semantic words based answer generator algorithm to improve accuracy of retrieved sentences. The proposed algorithm is experimented with the benchmark datasets, obtained results are compared and found that outer performs than other optimization algorithms.
previous article Personalized web page recommendation using case-based clustering and weighted association rule mining
next article Improved canny detection algorithm for processing and segmenting text from the images

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
Literature
1.
Miller, G.A.: WordNet: a lexical database for English. Commun. ACM 38(11), 39–41 (1995)CrossRef
2.
Liu, S., Liu, F., Yu, C., Meng, W.: An effective approach to document retrieval via utilizing WordNet and recognizing phrases. In: Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval. ACM, pp. 266–272 (2004)
3.
Bouras, C., Tsogkas, V.: A clustering technique for news articles using WordNet. Knowl.-Based Syst. 36, 115–128 (2012)CrossRef
4.
Li, Y., McLean, D., Bandar, Z.A., O’shea, J.D., Crockett, K.: Sentence similarity based on semantic nets and corpus statistics. IEEE Trans. Knowl. Data Eng. 18(8), 1138–1150 (2006)CrossRef
5.
Momtazi, S., Klakow, D.: Bridging the vocabulary gap between questions and answer sentences. Inf. Process. Manage. 51(5), 595–615 (2015)CrossRef
6.
Negi, Y.S., Kumar, S.: A comparative analysis of keyword-and semantic-based search engines. In: Intelligent Computing, Networking, and Informatics. Springer India, pp. 727–736 (2014)
7.
O’Shea, K.: An approach to conversational agent design using semantic sentence similarity. Appl. Intell. 37(4), 558–568 (2012)CrossRef
8.
Ramprasath, M., Hariharan, S.: Algorithm for answer extraction based on pattern learning. Int. Arab J. Inf. Technol. 13(1A), 178–183 (2016)
9.
Tanwar, P., Prasad, T.V., Datta, K.: An effective reasoning algorithm for question answering system. Int. J. Adv. Comput. Sci. Appl. Special issue on Natural language processing, pp. 52–57 (2014)
10.
Thangamani, M., Thangaraj, P.: Integrated clustering and feature selection scheme for text documents. J. Comput. Sci. 6(5), 536–541 (2010)CrossRef
11.
Wang, M.: A survey of answer extraction techniques in factoid question answering. Assoc. Comput. Linguist. 1(1), 1–14 (2006)
12.
Yang, X.S., Deb, S.: Cuckoo search via Lévy flights. In: Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on. IEEE, pp. 210–214 (2009)
13.
Yang, X.S., Deb, S.: Engineering optimisation by cuckoo search. Int. J. Math. Model. Numer. Optim. 1(4), 330–343 (2010)MATH
14.
Civicioglu, P., Besdok, E.: A conceptual comparison of the Cuckoo-search, particle swarm optimization, differential evolution and artificial bee colony algorithms. Springer, Artif. Intell. Rev. (2011)
15.
Perspectives on Educational Data Mining – A Study Published in Man in india
16.
Bhuvaneswari, M.: Nature inspired algorithms: a review. Int. J. Emerg. Technol. Comput. Sci. Electron. 12(1), 21–28 (2014)MathSciNet
17.
18.
Wu, Y., Hori, C., Kashioka, H., Kawai, H.: Leveraging social Q&A collections for improving complex question answering. Comput. Speech Lang. 29(1), 1–19 (2015)CrossRef
19.
Karpagam, K., Saradha, A.: An improved question answering system using domain context specific document clustering with Wordnet. Int. J. Print. Packag. Allied Sci. 4(5), 3257–3265 (2016)
20.
Balasubramanian, N., Allan, J., Croft, W.B.: A comparison of sentence retrieval techniques. In: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval. ACM, pp. 813–814 (2007)
21.
Echihabi, A., Hermjakob, U., Hovy, E., Marcu, D., Melz, E., Ravichandran, D.: How to Select an Answer String? Advances in Open Domain Question Answering, pp. 383–406. Springer, New York (2006)
22.
Liu, S., Liu, F., Yu, C., Meng, W: An effective approach to document retrieval via utilizing WordNet and recognizing phrases. In: Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval, ACM, pp. 266–272 (2004)
23.
Tan, M., dos Santos, C. N., Xiang, B., Zhou, B.: Improved Representation Learning for Question Answer Matching. In ACL (1) (2016)
24.
Schröder, G., Thiele, M., Lehner, W.: Setting goals and choosing metrics for recommender system evaluations. CEUR Workshop Proc 811, 78–85 (2011)
Metadata
Title
Intelligent sentence retrieval using semantic word based answer generation algorithm with cuckoo search optimization
Authors
Karpagam Kanagarajan
Saradha Arumugam
Publication date
23-02-2018
Publisher
Springer US
Published in
Cluster Computing / Issue Special Issue 3/2019
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-018-2054-x

Other articles of this Special Issue 3/2019

Cluster Computing 3/2019 Go to the issue

OriginalPaper

Improving medical diagnosis performance using hybrid feature selection via relieff and entropy based genetic search (RF-EGA) approach: application to breast cancer prediction

OriginalPaper

Fuzzy based approach for adaptivity evaluation of web based open source Learning Management Systems

OriginalPaper

Enhanced sentiment labeling and implicit aspect identification by integration of deep convolution neural network and sequential algorithm

OriginalPaper

The research on compensation algorithm of infrared temperature measurement based on intelligent sensors

OriginalPaper

Research on the factors affecting safety behavior based on interpretative structural modeling

OriginalPaper

Analysis and simulation of reliability of wireless sensor network based on node optimization deployment model

Premium Partner

    Image Credits