Paper Info
Title
Conceptual Modeling For Financial Investment With Text Mining
Abstract
Although text-mining, sentiment analysis, and other forms of analysis have been carried out on financial investment applications, a significant amount of associated research is ad hoc searching for meaningful patterns. Other research in finance develops theory using limited data sets. These efforts are at two extremes. To bridge the gap between financial data analytics and finance domain theory, this research analyzes a specific conceptual model, the Business Intelligence Model (BIM), to identify constructs and concepts that could be beneficial for matching data analytics to domain theory. Doing so, provides a first step towards understanding how to effectively generate and validate domain theories that significantly benefit from data analytics.
Year
DOI
Venue
2015
10.1007/978-3-319-25264-3_39
CONCEPTUAL MODELING, ER 2015
Keywords
Field
DocType
Text-mining, Big data, Small data, Conceptual modeling, Finance domain theory, Domain model, Business intelligence model (BIM)
Data science,Financial modeling,Data mining,Data analysis,Conceptual model,Computer science,Sentiment analysis,Domain theory,Finance,Business intelligence,Big data,Domain model
Conference
Volume
ISSN
Citations 
9381
0302-9743
0
PageRank 
References 
Authors
0.34
3
3
Name
Order
Citations
PageRank
Yang Gu101.69
Veda C. Storey22796542.19
Carson C. Woo329575.32