The objective of this thesis is to explore technologies and solutions and see if it is possible to make a logistical flow more efficient. The logistical flow consists of a database containing materiel for purchase or reparation. As of now, searches may either result in too many results, of which several are irrelevant, or no results at all. The search needs to be very specific to retrieve the exact item, which requires extensive knowledge about the database and its contents. Areas that will be explored include Natural Language Processing and Machine Learning techniques. To solve this, a literature study will be conducted to gain insights into existing work and possible solutions. Exploratory Data Analysis will be used to understand the patterns and limitations of the data.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-122960 |
| Date | January 2023 |
| Creators | Ellerblad Valtonen, David, Franzén, André |
| Publisher | Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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