Data Extraction Approach for Aggregator Platforms - Fadte, Anand (Digital Repository of Theses, 2024)
The purpose of this Research proposal is to find an optimal solution for data extraction for aggregator platforms, in this review, multiple research papers are involved with the pros and cons of using them. First, let us start by discussing the aggregator platform. So, what do we mean by the aggregator model? An aggregator business model is like a network model where a firm collects information about a particular good or service provider and it makes the provider their partner Gosh (Ghosh, 2022, p. 1). Some of the companies which are using the aggregator business model are Amazon, Flipkart, etc. (Ecommerce, n.d.). Now, here are the advantages of using this model. First, it is very cost-effective and consumes a very less amount of time to set up, there is no inventory cost involved in this instead, the company which owns that platform can focus more on marketing and user experience Miles (Miles, 2022, p. 2). But there are challenges with this type of business model too, the very first challenge which comes is the dependency on other platforms such as Google, Facebook, etc. If tomorrow they launch their platform, then they can change their algorithm and show ads and rank their website on top. The other challenge is accumulating data from various sites, and companies on a single platform. Apart from API, scraping data from various websites and presenting it on the portal is also a challenging task. So, what are the major solution approaches that I will be discussing in this Research proposal? Using techniques such as Simple Object Access Protocol (SOAP) and Representational State Transfer (REST) to generate Application Programming Interfaces. Computer Vision (CV) and Natural Language Processing (NLP) extract essential information from any source. In today's fast-paced digital world, staying up-to-date with the latest website changes is crucial for various reasons, including staying competitive, ensuring the accuracy of information, and maintaining compliance with regulations. However, the dynamic nature of online content makes it challenging to keep track of every minute change that occurs. Fortunately, advancements in technology, particularly in the field of computer vision, offer solutions to address this issue. The development of a system capable of monitoring changes on websites in near this system can analyse specific web pages and detect any alterations that occur within them. This approach involves capturing screenshots of the targeted web pages at regular intervals and comparing them to identify differences. One of the key components of this system is its ability to focus on specific links or sections of websites based on predefined criteria. 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