Clustering of Financial Documents for structure Detection and Future Feature Learning
- In today’s market, the process of dealing with textual data for internal and external processes has become increasingly important and more complex for certain companies. In this context,the thesis aims to support the process of analysis of similarities among textual documents by analyzing relationships among them. The proposed analysis process includes discovering similarities among these financial documents as well as possible patterns. The proposal is based on the exploitation and extension of already existing approaches as well as on their combination with well-known clustering analysis techniques. Moreover, a software tool has been implemented for the evaluation of the proposed approach, and experimented on the EDGAR filings, on the basis of qualitative criteria.
Author: | Adnan Siddique |
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Advisor: | Kristan Schneider, Alrik Messner |
Document Type: | Master's Thesis |
Language: | English |
Year of Completion: | 2019 |
Granting Institution: | Hochschule Mittweida |
Release Date: | 2021/03/03 |
GND Keyword: | Dokumentverarbeitung; Cluster-Analyse |
Institutes: | Angewandte Computer‐ und Biowissenschaften |
DDC classes: | 519.53 Datenanalyse, Cluster-Analyse |
Open Access: | Frei zugänglich |
Licence (German): | Urheberrechtlich geschützt |