Abstract
For using system, under the need of getting quickly access to store and retrieve information Document store type of NoSQL database becoming important elements in the large-scale storage system and for real-time interactive tasks. An automated approach is presented to generate document store from NLP. The presented approach works to get inputs a piece of English specification according to requirements and our presented approach is capable to transforms input text to NLP based generation of document store. Our proposed system can generate the unambiguous and consistent result according to user requirements on NLP based generation of document store.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Atzeni, P., Bugiotti, F., Cabibbo, L., Torlone, R.: Data modeling in the NoSQL world. Comput. Stand. Interfaces (2016)
Bugiotti, F., Cabibbo, L., Atzeni, P., Torlone, R.: A Logical Approach to NoSQL Databases (2013)
Barbierato, E., Gribaudo, M., Iacono, M.: Performance evaluation of NoSQL big-data applications using multi-formalism models. Future Gener. Comput. Syst. 37, 345–353 (2014)
Cattel, R.: Scalable SQL and NoSQL data stores. ACM SIGMOD Rec. 39(4), 12–27 (2011)
Cudré-Mauroux, P., et al.: NoSQL databases for RDF: an empirical evaluation. In: Alani, H., et al. (eds.) ISWC 2013. LNCS, vol. 8219, pp. 310–325. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-41338-4_20
Curl command (n.d.). http://docs.couchdb.org/en/2.0.0/intro/curl.html. Accessed 28 Apr 2018
Damaiyanti, T.I., Imawan, A., Kwon, J.: Extracting trends of traffic congestion using a NoSQL database. In: 2014 IEEE Fourth International Conference on Big Data and Cloud Computing (BDCloud), pp. 209–213. IEEE, December 2014
Document database (n.d.). https://en.wikipedia.org/wiki/Document-oriented_database. Accessed 20 Mar 2018
Goyal, A., Swaminathan, A., Pande, R., Attar, V.: Cross platform (RDBMS to NoSQL) database validation tool using bloom filter. In: 2016 International Conference on Recent Trends in Information Technology (ICRTIT), pp. 1–5. IEEE, April 2016
Hadjigeorgiou, C.: RDBMS vs NoSQL: performance and scaling comparison. MSc in High (2013)
Jatana, N., Puri, S., Ahuja, M., Kathuria, I., Gosain, D.: A survey and comparison of relational and non-relational database. Int. J. Eng. Res. Technol. 1(6) (2012)
Klettke, M., Störl, U., Scherzinger, S.: Schema extraction and structural outlier detection for JSON-based NoSQL data stores. In: Datenbanksysteme für Business, Technologie und Web (BTW 2015) (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Sana, T., Shafiq, O. (2019). A Natural Language Based Approach to Generate Document Stores. In: Bajwa, I., Kamareddine, F., Costa, A. (eds) Intelligent Technologies and Applications. INTAP 2018. Communications in Computer and Information Science, vol 932. Springer, Singapore. https://doi.org/10.1007/978-981-13-6052-7_31
Download citation
DOI: https://doi.org/10.1007/978-981-13-6052-7_31
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-6051-0
Online ISBN: 978-981-13-6052-7
eBook Packages: Computer ScienceComputer Science (R0)