News: Automatic IAB Content Classification Model

Introduction

We are excited to announce our IAB Content Classification Model, our advanced, highest-performing IAB Classification Model designed to tag content, ad copy, and marketing campaigns by IAB content codes. This cutting-edge model leverages the latest in machine learning and natural language processing to seamlessly convert unstructured text into standardized IAB codes, ensuring accuracy and streamlined ad operations workflows.

IAB Classification Overview

The IAB Classification Model is a powerful tool for automatically tagging content with IAB codes. It can accurately classify a wide range of text, from articles and blog posts to ad copy and marketing campaigns with multiple content codes (ordered by confidence score). This model is designed to help publishers, advertisers, and ad tech companies streamline their content tagging workflows and improve the efficiency of their ad operations, including providing enriched metadata for ad targeting, audience segmentation, and content recommendation to Google Ad Manager.

For Business & Product Managers: IAB Classification Model

Business and product teams can leverage the IAB Classification Model to enhance their ad products and services. By integrating our model into your applications, you can automate the content coding process, reduce errors, and improve the efficiency of operations. Our model is designed to handle a wide range of text, from short ad copy to long-form articles, providing accurate and reliable IAB codes for your content.

To get started with the IAB Classification Model, sign in and start classifying with ease via the user interface. You can also run a batch classification job on a file of your ad copy or publisher content to tag it with IAB codes. Our model is designed to handle large volumes of text, ensuring that you can process your content quickly and efficiently.

For Developers: IAB Classification Model API

Classifying text is as simple as hitting a model endpoint. You can use the Taylor API to classify with IAB codes in real-time. Here's an example of how you can use the model to classify a text:

import requests
api_key = "xx-your-api-key-here"
 
res = requests.post(
    "https://api.trytaylor.ai/api/public_classifiers/predict",
    headers={"Authorization": f"Bearer {api_key}"},
    json={
        "model": "iab_content",
        "texts": [
                "Jennifer Lopez Has Officially Filed For Divorce From Ben Affleck, So Here’s Everything We Know So Far: Jen filed for divorce on the second anniversary of her and Ben's Georgia wedding, which insiders believe 'speaks a ton' about the split.",
        ],
        "threshold": 0.5,
        "top_k": 3
    }
)
 
print(res.json())

Using this code, you can get IAB codes. Your specified threshold and top_k values will determine the number of codes returned. For example, if you wish to only get the top code, you can set top_k to 1.

Integrations & Deployment

Try the IAB Classification Model today. Sign in here to start classifying for free on your first 1,000 texts.

The IAB Classification Model can be seamlessly integrated with your existing CMS, CRM, and applications. Whether you are an ad ops professional, an editor, or an advertiser, you can leverage the power of our model to streamline your tagging and content coding processes.