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# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
Prospectus text mining is very important for the investor community to identify major risks.
factors and evaluate the use of the amount to be raised during an IPO. For this dataset author
downloaded 100 prospectuses from the Indian Market Regulator website. The dataset contains the URL and OCR text for 100 prospectuses.
Further, the author released a Roberta LM and sentence transformer for usage.
### Supported Tasks and Leaderboards
N.A.
### Languages
ENGLISH
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
There are 4 columns:
title_prospectus: Title of the IPO prospectus
href_prospectus: Location of HTML
pdf_prospectus : Pdf of prospectus
content_whole_prospectus: OCR text for the whole prospectus
### Data Splits
N.A.
## Dataset Creation
### Curation Rationale
Prospectus text mining
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
This will help investors and the merchant bank community explore prospectuses in a more automated way, thus saving time.
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
```bibtex
@misc{ROBERTA GOES FOR IPO: PROSPECTUS ANALYSIS WITH LANGUAGE MODELS FOR INDIAN INITIAL PUBLIC OFFERINGS,
author = {Abhishek Mishra and Yogendra Sisodia},
title = {ROBERTA GOES FOR IPO: PROSPECTUS ANALYSIS WITH LANGUAGE MODELS FOR INDIAN INITIAL PUBLIC OFFERINGS},
year = {2022},
url = {https://aircconline.com/csit/papers/vol12/csit121905.pdf},
}
```
### Contributions
Made by Author [Scholarly360](https://github.com/Scholarly360).