Performed Web Labeling for an Israeli Advertising Company
Labeled 35K+ websites under different categories within a period of 3 months only.
The company is a professional and efficient web labeling & advertising service provider, based in Israel. It offers budget-friendly advertising solutions to brands across the globe along with its core intelligence solutions. The company was founded 10 years before by a group of Israeli intelligence units. Over the years, the company gained a reputation for providing its amazing intelligence solutions.
With the incorporation of advanced ML (Machine Learning) algorithms, the company is involved in developing bots. These bots can perform many automated tasks including anomaly detection. Therefore, with the help of these bots, the company can easily detect negative brand content and fake traffic consolidation. Besides that, they can also identify fake users on the website in a few minutes due to its strong ML codes. To make these bots further improved, the company needed efficient data labeling services. Hence, AskdataEntry approached the company with relevant sample files and attracted them to its solutions.
Importance of Web Labeling Services for Website Labelling and Advertising Companies
Website labeling companies, especially those involved in developing ML models, need the help of data labeling services. The first step in developing a robust ML model is accurate data labeling. Proving precision-based training for each dataset is essential to getting high-quality ML training datasets. With the help of efficient web labeling, ML models can get proper training with accurate measures.
Usually, the team of data annotators uses the most up-to-date cutting-edge tools to train the datasets. ML models not only provide automated functions but also help in making decisions thus proving accurate training is essential here. In most cases, ML training dataset developers outsource data labeling services from expert companies. Outsourcing fits their budgets and also provides flexibility in adoption. Also, it makes the ML models efficient and strong in terms of showing accurate results.
Challenges Faced by the Company
The company is a web labeling and advertisement service provider that has a separate team for the labeling work. Despite having a dedicated team, the company faced many challenges regarding its data labeling process. The challenges are;
The company was involved in a project where it identified the negative content of a website using ML models. The task of the data labelers was to identify the negative content and categorize it under three divisions. These three categories are negative, sensitive, and OK. Accurately categorizing the divisions of websites was the target of the internal team. However, they often mixed different tags or annotated the websites under the wrong tags. Hence, the company wanted to partner with an efficient company that could provide correct categorization and remove all bias.
To make the ML model work accurately in detecting negative content, the company needed to label 45K+ websites. The internal team was not efficient enough to handle this number of bulk work. The team only be able to label 10K websites in a span of 4 months, which was very little. On the other hand, the company wanted to initiate the project as early as possible. So, it became very tough to complete the rest of the work without the help of an outsourcing agency.
Developing bots for identifying anomalies is not a one-time process rather it needs frequent updates. However, the company’s internal team was so involved in the labeling process that it had no time for updates. Hence, the efficiency of the ML model decreased over a period due to ignoring the updating process. Therefore, the company wanted to have a process that could efficiently handle the updates of the ML models on time.
Custom Solutions from AskDataEntry
With the application of cutting-edge tools, we labeled each data from the website under different tags. We followed our efficient techniques to deliver our robust solutions to the company directly. Following the step-by-step method helped us here in providing accurate solutions to the company .
Requirement Analysis and Trial Run
We started the project by thoroughly understanding the requirements of the client. Our team has connected to the client under a direct communication model. It helped us understand the entire project thoroughly and efficiently without any confusion. After understanding the project requirements, we performed a trial run to show our efficiency. We trained one of our team members for this trial project and dedicated one day to completing it. The member has efficiently labeled 75 websites with different tags for the trial project.
We delivered the trial project within 24 hours and gained the trust of our client with our service. The client was impressed by our dedicated work and decided to sign the entire contract. By making no delay, we grabbed the opportunity and accepted the contract.
Categorized Websites using Efficient Tools
With the help of cutting-edge tools, we categorized websites under different tags. As per the client’s instruction, we tagged a website as Negative if we found any bad or vulgar content there. On the other hand, we tagged a website as OK if we did not find any vulgarity in that web content. Here content means the texts, images, videos, graphics, and audio data. Interestingly, the tag sensitive we used when we found some portion of the website was vulgar but the rest were good.
Trained Resources
Labeling 35K+ websites within three months under different categories was challenging for us. However, with the help of our client-provided training session, we easily performed the job. We provided training to our team with training modules that the client provided to us. Our team efficiently understood which tag to use to categorize the websites.
Project Division
We distributed the project under different divisions to complete the entire thing on time. A total of 35K+ websites we had to cover under a strict timeframe for this project. Thus, we distributed the websites under three baches where each batch contains 12K websites. We targeted to complete each batch each month and finish all bathes within the stipulated deadline.
Timely Delivered
Distributing the websites under three batches helped us to complete the project within a fixed time frame. The client demanded the project to be completed within three months and hence we delivered the files within that period. After completing each batch, we delivered the files immediately. This way we maintained the deadline and accuracy of the project, both at the same time.
Neil R.
We are very satisfied with the services of AskDataEntry for our project. The company has provided us with data labeling services with complete accuracy. Even at delivering the services, the company delivered the services accurately before the deadline. Overall, the company has done a very good job and kept its promises.
