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Data Mining Technique for Temporal Association Mining using SPN-Sigmoid Neural Networks

Vaishali Sahu1 , Anubhav Sharma2 , Anshul Sarawagi3

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-5 , Page no. 1459-1465, May-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i5.14591465

Online published on May 31, 2019

Copyright © Vaishali Sahu, Anubhav Sharma, Anshul Sarawagi . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Vaishali Sahu, Anubhav Sharma, Anshul Sarawagi, “Data Mining Technique for Temporal Association Mining using SPN-Sigmoid Neural Networks,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.5, pp.1459-1465, 2019.

MLA Style Citation: Vaishali Sahu, Anubhav Sharma, Anshul Sarawagi "Data Mining Technique for Temporal Association Mining using SPN-Sigmoid Neural Networks." International Journal of Computer Sciences and Engineering 7.5 (2019): 1459-1465.

APA Style Citation: Vaishali Sahu, Anubhav Sharma, Anshul Sarawagi, (2019). Data Mining Technique for Temporal Association Mining using SPN-Sigmoid Neural Networks. International Journal of Computer Sciences and Engineering, 7(5), 1459-1465.

BibTex Style Citation:
@article{Sahu_2019,
author = { Vaishali Sahu, Anubhav Sharma, Anshul Sarawagi},
title = {Data Mining Technique for Temporal Association Mining using SPN-Sigmoid Neural Networks},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2019},
volume = {7},
Issue = {5},
month = {5},
year = {2019},
issn = {2347-2693},
pages = {1459-1465},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4430},
doi = {https://doi.org/10.26438/ijcse/v7i5.14591465}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i5.14591465}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4430
TI - Data Mining Technique for Temporal Association Mining using SPN-Sigmoid Neural Networks
T2 - International Journal of Computer Sciences and Engineering
AU - Vaishali Sahu, Anubhav Sharma, Anshul Sarawagi
PY - 2019
DA - 2019/05/31
PB - IJCSE, Indore, INDIA
SP - 1459-1465
IS - 5
VL - 7
SN - 2347-2693
ER -

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Abstract

Data mining is a methodology that takes information as information and yields learning. Such information objects, which are overwhelming not quite the same as or conflicting with the staying set of information, are called exceptions. An anomaly is an informational index which is not quite the same as the rest of the information. In recent research extraction of temporal information that too in specific medical domain came into significance, where the different research performed in this segment. In existing work paper CRF based technique which is conditional random field’s model is used. They achieved best f-measure, accuracy and precision parameters while comparing with other approach such as Baseline, CRF+ Lexical is used. The future work remain by the research is developing of semi-supervised scheme for the temporal extraction and also working with un-annotated data text to make it annotating and thus obtaining better precision, recall, accuracy and F- Measure values.

Key-Words / Index Term

Rule Mining, Classification, Data Mining Algorithms, K-Theory

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