Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Predicting the Stock Markets Using Neural Network with Auxiliary Input Subject The topic of the resource Deep learning; Prediction; Stock market; Text classification Description An account of the resource Predicting the stock market has always been a challenging task and has always had a certain appeal for researchers all around the world. Stock markets are supposed to be quite random and people with experience in the market strongly agree to the fact. Thus, predicting the stock market accurately paves the way for endless money. To date, no such algorithm has been devised that could even predict the stock market with a 90% accuracy rate. The difficulty lies in the randomness of the markets, and the various complexities involved in modeling market dynamics. Nevertheless, there have been algorithms with a decent success rate and researchers around the world have been in a constant attempt to improve over them. Thus, through this paper we attempt at predicting the return of a stock over a period of 10days after a particular news was out regarding the stock using the headlines of the news and certain other features important in determining the direction of a stock. The model was implemented with a sigma score of 0.81. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Sakshi; Ghosh S. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-190, pp. 743-752. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2021-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-16-0882-7_66" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-16-0882-7_66</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112245198&amp;doi=10.1007%2F978-981-16-0882-7_66&amp;partnerID=40&amp;md5=a27282907642831cc1b0eadea6b85a6a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112245198&amp;doi=10.1007%2f978-981-16-0882-7_66&amp;partnerID=40&amp;md5=a27282907642831cc1b0eadea6b85a6a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981160881-0 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Sakshi, Computer Science and Engineering, Siddaganga Institute of Technology, Tumkur, India; Ghosh S., Computer Science and Engineering, Christ University, Bangalore, India