Authors :
Tamilselvan Arjunan
Volume/Issue :
Volume 7 - 2022, Issue 9 - September
Google Scholar :
https://bit.ly/3IIfn9N
Scribd :
https://bit.ly/3rHIR1y
DOI :
https://doi.org/10.5281/zenodo.7171791
Abstract :
The goal of the Business Intelligence data
extractor (BID- Extractor) tool is to offer high-quality,
usable data that is freely available to the public. To assist
companies across all industries in achieving their
objectives, we prefer to use cutting-edge, businessfocused web scraping solutions. The World wide web
contains all kinds of information of different origins;
some of those are social, financial, security, and
academic. Most people access information through the
internet for educational purposes. Information on the
web is available in different formats and through
different access interfaces. Therefore, indexing or
semantic processing of the data through websites could
be cumbersome. Web Scraping/Data extracting is the
technique that aims to address this issue. Web scraping
is used to transform unstructured data on the web into
structured data that can be stored and analyzed in a
central local database or spreadsheet. There are various
web scraping techniques including Traditional copy-andpaste, Text capturing and regular expression matching,
HTTP programming, HTML parsing, DOM parsing,
Vertical aggregation platforms, Semantic annotation
recognition, and Computer vision webpageanalyzers.
Traditional copy and paste is the basic and tiresome web
scraping technique where people need to scrap lots of
datasets. Web scraping software is the easiest scraping
technique since all the other techniques except
traditional copy and pastes require some form of
technical expertise. Even though there are many webs
scraping software available today, most of them are
designedto serve one specific purpose. Businesses cannot
decide using the data. This research focused on building
web scraping software using Python and NLP. Convert
the unstructured data to structured data using NLP. We
can also train the NLP NER model. The study's findings
provide a way to effectively gauge business impact.
The solution has a greater impact when applied to:
Analyzing companies’ fundamentals
Analyzing better deal opportunities.
The goal of the Business Intelligence data
extractor (BID- Extractor) tool is to offer high-quality,
usable data that is freely available to the public. To assist
companies across all industries in achieving their
objectives, we prefer to use cutting-edge, businessfocused web scraping solutions. The World wide web
contains all kinds of information of different origins;
some of those are social, financial, security, and
academic. Most people access information through the
internet for educational purposes. Information on the
web is available in different formats and through
different access interfaces. Therefore, indexing or
semantic processing of the data through websites could
be cumbersome. Web Scraping/Data extracting is the
technique that aims to address this issue. Web scraping
is used to transform unstructured data on the web into
structured data that can be stored and analyzed in a
central local database or spreadsheet. There are various
web scraping techniques including Traditional copy-andpaste, Text capturing and regular expression matching,
HTTP programming, HTML parsing, DOM parsing,
Vertical aggregation platforms, Semantic annotation
recognition, and Computer vision webpageanalyzers.
Traditional copy and paste is the basic and tiresome web
scraping technique where people need to scrap lots of
datasets. Web scraping software is the easiest scraping
technique since all the other techniques except
traditional copy and pastes require some form of
technical expertise. Even though there are many webs
scraping software available today, most of them are
designedto serve one specific purpose. Businesses cannot
decide using the data. This research focused on building
web scraping software using Python and NLP. Convert
the unstructured data to structured data using NLP. We
can also train the NLP NER model. The study's findings
provide a way to effectively gauge business impact.
The solution has a greater impact when applied to:
Analyzing companies’ fundamentals
Analyzing better deal opportunities.
