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Web Scraping

Web Scraping

The rapid growth of information, such as texts and photos, on the web where information is continuously updated and various applications making use of this data motivates the need for efficient and effective real time approaches to identify, retrieve, and process such information. 

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Web scraping is the process of automatically finding and collecting information from the World Wide Web and turning the information into data that can be used by a computer, database or application. But as the data on the web are constantly changing, Web scraping is a real challenge.

Most of the time, manually monitoring and extraction of useful data is really a time consuming operation and can be inefficient and prone to error. But, data scientists prefer to apply some automatic scalable web data extraction programs to do this job rapidly and precisely.

In yomoBit, we have connections to several text miner, NLP scientists, and machine learning experts who work with our company as consultant and they can help you to choose the best automatic data extraction programs based on your requirements and conditions. In addition, several developers who are familiar with languages such as Python, C/C++, Perl, Java, and PHP have collaboration with yomoBit to design and implement our customer’s projects.
In the past years, we have gained much more experiences in extraction information from a given number of structured and un-structured data sources, e.g. Web pages, Excel files, and RSS feeds, and now we are ready to offer our experiences under our new company, yomoBit.
The main aim of yomoBit is:
To design and implement accurate, fast, reliable, and effective real-time data retrieval methods, for both structured and un-structured data sources, to extract and grab large quantities of external and mostly unstructured web data into structured data feed from one or more pages or Website in minutes for optimal data usage.

To filter, sort, categorize, and classify extracted data using high-tech methods according to your requirements and demands. Without any doubt, after analyzing your data you will find many hidden facts about your company and your competitors.

To use valuable extracted datasets for further processing such as data mining, text classification, trend mining, and data visualization.

To integrate modules to the pipeline data processing or to let you to use our methods as a preprocessing phase in your projects.

To export daily extracted data to several data types you may use, e.g. CVS, XML, JSON, and XLS files.

To provide several dynamically reports based on raw or processed extracted data for your business and market for better decisions.

To design a simple point-and-click interface