How does AI enhance web data gathering?
Contents of article:
- Data collection, geo targeted proxies, and AI
- How is AI applied?
- How is AI-enhanced data harvesting organized?
- The future of AI in data collection sphere
Collecting accurate web data at scale in 2023 is the most valuable method of application for the whole potential of Dexodata, the enterprise gathering infrastructure. Even the absence of professional coding skills is no more an obstacle for those who buy dedicated proxies from a trusted proxy website. But an AI-driven model is a step-change in data extraction.
Data collection, geo targeted proxies, and AI
Artificial intelligence (AI) is the ability of the machine to analyze its experience and learn by it similarly to human behavior. The longer AI operates, the more efficient it becomes in performing a task. In our case, it obtains and manages large quantities of information via geo targeted proxies much faster and more accurately than a team of professionals.
The term Machine Learning (ML) expresses the internal process of AI processing data and evolving without direct orders of an operator. Deep Learning, in turn, is a single method of ML involving neural networks.
How is AI applied?
Data extraction stands for collecting particular particles of knowledge for raising business awareness. Considering the volume of knowledge needed in 2023 to stay ahead of the rivals, the process is automated. Algorithms visit sites one by one and gather information, from prices to patterns of clients’ behavior. Then it is compiled, structured and presented for further analysis. Rotating datacenter proxies are responsible for maintaining the connections between end-user and websites’ servers.
AI-based algorithms are taught to:
- Find common patterns
- Generalize similar actions
- Perform the job reliably
- Analyze its results
- Apply the experience to the following pages.
AI-driven software robots perform the routine procedures faster and more precisely. They take into account specifics of the content, its location and the security measures taken by the target website.
How is AI-enhanced data harvesting organized?
Every case is broken into the stages:
- Crawling and obtaining accurate URLs
- Developing the main and applicable algorithms
- Utilizing proxies, e.g. buying residential IP addresses, mobile or datacenter ones and setting them up
- Extracting information and maintaining the process
- Processing and checking data to its final applicable form.
Artificial intelligence takes every step according to its parameters, even finds the most suitable geo targeted proxies for every website from the HTTPS proxy list.
The main goal of an AI-orientated approach is to pass all recurrent actions to automated programs. Let’s have a look at every phase in detail.
1. Crawling and obtaining accurate URLs
The first thing we do manually is forming a database of URL addresses. These are not ways to landing pages, but accurate IPs leading to the required things. Product characteristics, lead data, etc. have particular places to be extracted from. As any rotating datacenter proxy has external IP introduced to the third-party servers.
AI gets a library of proper URLs at the beginning of the work and studies it via ML. The algorithm is intended to:
- Get the value of site’s partition
- Assign label to it and other similar info categories
- Aggregate the needed pieces from the source pages
- Check and correct the data amounts gathered
- Interpret and present it as a ready-to-go product, e.g. as XLS or CSV databases.
AI-engaged algorithms not only compile lists of addresses faster, but also do it on their own. No need to handle every source manually.
The most trusted proxy websites are compatible with AI-orientated solutions due to API-methods. The third-party software rotates external addresses, obtains new ports of proxies, geo targeted in the particular city, and so forth.
2. Developing the main and applicable algorithms
Automated solutions are created considering different elements to succeed in data acquiring. Among them are suitable languages, libraries and frameworks. Another issue is to determine proper file type and HTML class, incl. multimedia, and extract it in a proper manner to the right place.
AI is trained to:
- Read both static and dynamic content
- Respect site’s user policy
- Obtain rotating datacenter proxies, residential or mobile depending on the target page specifics
- Detect mistakes or malfunctions and handle them.
3. Utilizing proxies
The challenge of utilizing proxies properly lays on AI-driven applications. Engineering team just makes a choice of the platform, where one can buy residential IP. Then the AI robot gets the API keys to connect and manage IP addresses on the automated level.
It saves a lot of time in comparison with conventional data harvesting. Trusted proxy websites such as Dexodata are fully-compatible with such solutions. Our best datacenter proxies have at least 10 credible reasons to be bought and applied.
4. Extracting information from the Web
AI automation shows positive results on collecting both structured and unstructured data. It is applicable to XML and JSON formats. Electronic brain also recognizes and deciphers handwritten texts in addition to OCR (Optical Character Recognition) after a proper training.
Artificial intelligence bypasses anti-botting measures, which threaten to interrupt the ongoing procedure. Additional modules may be deployed to avoid certain checks, such as reCAPTCHA.
Automated robots combine geo targeted proxies with proper digital fingerprints and simulate common user’s behavior on pages according to the complex templates the AI was taught on. It reduces the time needed for the job. Buy residential and mobile proxies at our advice, or datacenter.
AI-based solutions enhance the average speed, volumes, accuracy, and efficiency of web data collection
Data obtaining solutions based on ML discover altered content or duplicated files easily. Errors are rectified, and AI learns to avoid them down the road.
5. Processing and checking data
Procedure performed manually takes a lot of time and human resources hence this operation is delivered to AI-based scrapers. They do the following:
- Clean the gathered information
- Identify it
- Validate data
- Define a category and tag it
- Direct the information for further use.
AI-oriented system solutions are mistaken earlier than human employees. They adapt its tools to obtain information from thousands of separate web pages without direct control.
The future of AI in data collection sphere
Software solutions based on artificial intelligence are developing rapidly. The global AI market in 2023 is estimated at almost $120 billion, according to the market analytics from Precedence Research. The AI-powered systems for data collection showed an increase to the level of $4 billion.
Artificial intelligence seems promising for the industry of gathering online information and managing it. These automated algorithms:
- Boost the gathering process
- Spare time and budgets
- Provide more accurate results
than conventional ways of obtaining selected information from hundreds and thousands of pages.
A trusted proxy website, Dexodata is also a reliable load-resistant infrastructure for collecting and processing data at scale. We offer a free trial of our rotating datacenter proxies, residential and mobile — for your business to stay in trend.
