Automated market trends detection with machine learning
| dc.contributor.author | Nguyen, Hieu, author | |
| dc.date.accessioned | 2019-11-14T16:56:14Z | |
| dc.date.available | 2019-11-14T16:56:14Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | The goal of the project is to create an automated process for detecting growing technologies in the IT sphere using open data. The process consists of 3 main steps. First, online media texts are collected. A model is trained to output a list of topics that appears on the media and are relevant our hi-tech interests. Second, Google search volume time-series for each relevant topic is retrieved. These time-series indicate the topic popularity over time.Third, a machine learning model is trained to automatically recognize whether a Google search volume time-series has consistent growth pattern. This process eventually provides a list of topics whose popularity grows consistently over time. The main contribution of this work lies in the vastly reduced amount of time spent on market research that an analyst normally needs. This process can also be used to search for trends in different industries other than hi-tech. | en_US |
| dc.format.medium | born digital | |
| dc.format.medium | Student works | |
| dc.format.medium | posters | |
| dc.identifier.uri | https://hdl.handle.net/10217/198727 | |
| dc.language | English | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | Colorado State University. Libraries | en_US |
| dc.relation.ispartof | 2019 Projects | |
| dc.rights | Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright. | |
| dc.subject | machine learning | |
| dc.subject | market trend | |
| dc.title | Automated market trends detection with machine learning | en_US |
| dc.title.alternative | 197 - Hieu Nguyen | |
| dc.title.alternative | Automated process of detecting positive market trends using deep learning | |
| dc.type | Image | |
| dc.type | Text | en_US |
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