Top Free Topic/Entity Extraction tools, APIs, and Open Source models

Top Free Topic/Entity Extraction tools, APIs, and Open Source models

What is Topic Extraction API?

Topic Extraction API, also called Entity Extraction or Content Taxonomy, uses natural language processing to identify the main ideas and concepts in a text and group them into meaningful topics.It then returns a list of topics with their associated keywords or phrases.

This technology can analyze different types of text data, such as articles, social media posts, customer reviews and others. The Topic Extraction API has many uses, including organizing content, gauging emotions, identifying trends, and optimizing search engines.

It's important to highlight that the Topic Extraction API is immediately available for use, as opposed to Custom Text Classification, which necessitates a dataset prior to implementation.

Top Open Source (Free) Entity Extraction models on the market

For users seeking a cost-effective engine, opting for an open-source model is the recommended choice. Here is the list of the best Entity Extraction Open Source Models:

1‍. Genism

Gensim is a prevalent open-source tool in Python for topic modeling. It implements various efficient algorithms for modeling topics, like Latent Dirichlet Allocation (LDA) and Latent Semantic Analysis (LSA). Further, it features a user-friendly interface that simplifies training and using topic models.

2. scikit-learn

Scikit-learn is a Python library for machine learning that provides different topic modelling methods, including Latent Dirichlet Allocation (LDA), Non-Negative Matrix Factorisation (NMF), and Latent Semantic Analysis (LSA).

3. BERTopic

BERTopic is a method for extracting topics that uses BERT embeddings to enhance the process. It is constructed on the Hugging Face Transformers library.

4. Top2Vec

Top2Vec is an algorithm that combines topic modeling and document embeddings. It's designed to discover topics in large document collections.

5. Mallet

MALLET is a Java program that assists in processing language for things such as topic modeling. You can use it for different text tasks because it can implement a variety of machine learning algorithms, including Latent Dirichlet Allocation (LDA), which is useful for topic modeling.

6. tomotopy

Tomotopy is a topic modeling library for Python that supports various algorithms, including Latent Dirichlet Allocation (LDA), Hierarchical Dirichlet Process (HDP), and more. It provides an easy-to-use interface for topic modeling tasks.

7. BTM

BTM is a technique for discovering topics in short texts. It models biterms, which are when two words appear together in a short context. This method is especially helpful for short documents.

Cons of Using Open Source AI models

‍While open source models offer many advantages, they also have potential drawbacks and challenges. Here are some cons of using open source models:

  • Not Entirely Cost Free: Open-source models, while providing valuable resources to users, may not always be entirely free of cost. Users often need to bear hosting and server usage expenses, especially when dealing with large or resource-intensive data sets.
  • Lack of Support: Open source models may not have official support channels or dedicated customer support teams. If you encounter issues or need assistance, you might have to rely on community forums or the goodwill of volunteers, which can be less reliable than commercial support.
  • Limited Documentation: Some open source models may have incomplete or poorly maintained documentation. This can make it difficult for developers to understand how to use the model effectively, leading to frustration and wasted time.
  • Security Concerns: Security vulnerabilities can exist in open source models, and it may take longer for these issues to be addressed compared to commercially supported models. Users of open source models may need to monitor for security updates and patches actively.
  • Scalability and Performance: Open source models may not be as optimized for performance and scalability as commercial models. If your application requires high performance or needs to handle a large number of requests, you may need to invest more time in optimization.

Why choose Eden AI?

Given the potential costs and challenges related to open-source models, one cost-effective solution is to use APIs. Eden AI smoothens the incorporation and implementation of AI technologies with its API, connecting to multiple AI engines.

Eden AI presents a broad range of AI APIs on its platform, customized to suit your specific needs and financial limitations. These technologies include data parsing, language identification, sentiment analysis, logo recognition, question answering, data anonymization, speech recognition, and numerous other capabilities.

To get started, we offer free $10 credits for you to explore our APIs. 60720 (1).png

Access Topic Extraction providers with one API

Our standardized API enables you to integrate Topic Extraction APIs into your system with ease by utilizing various providers on Eden AI. Here is the list (in alphabetical order):

  • Google
  • IBM
  • OpenAI
  • Tenstorrent

1. Google Cloud- Available on Eden AI

Google Cloud uses advanced machine learning algorithms to extract important topics and details from text data. The API can process different kinds of documents, like web pages, articles, and social media posts. Google's solution can handle large amounts of data and delivers accurate results in multiple languages.

2. IBM- Available on Eden AI

IBM's Entity Extraction applies machine learning algorithms and NLP techniques to identify significant ideas, objects, and emotions in given text. Customers can use IBM's expertise to handle vast amounts of data and take advantage of multilingual assistance in examining text in various languages.

3. OpenAI- Available on Eden AI

OpenAI's technology relies on the advanced GPT-3.5 system to achieve high precision and trustworthiness by understanding the input's context. By receiving extensive instruction on substantial datasets, OpenAI's Topic Extraction API assures relevant outcomes, including those involving elaborate and nuanced text.

4. Tenstorrent- Available on Eden AI

Tenstorrent's solution uses advanced deep learning methods to accurately identify and categorize topics, resulting in more significant and useful insights. The Tenstorrent Topic Extraction API enables users to easily understand the crucial themes within a given document or dataset, keeping track of trends and changes over time.

Furthermore, the solution provided by Tenstorrent allows for customization at a significant level, enabling users to amend the API's parameters to fit their individual needs.

Pricing Structure for Topic Extraction API Providers

Eden AI offers a user-friendly platform for evaluating pricing information from diverse API providers and monitoring price changes over time. As a result, keeping up-to-date with the latest pricing is crucial. The pricing chart below outlines the rates for smaller quantities for November 2023, as well as you can get discounts for potentially large volumes.

How Eden AI can help you?

Eden AI is the future of AI usage in companies: our app allows you to call multiple AI APIs.
  • Centralized and fully monitored billing on Eden AI for Topic Extraction APIs
  • Unified API for all providers: simple and standard to use, quick switch between providers, access to the specific features of each provider
  • Standardized response format: the JSON output format is the same for all suppliers thanks to Eden AI's standardization work. The response elements are also standardized thanks to Eden AI's powerful matching algorithms.
  • The best Artificial Intelligence APIs in the market are available: big cloud providers (Google, AWS, Microsoft, and more specialized engines)
  • Data protection: Eden AI will not store or use any data. Possibility to filter to use only GDPR engines.

You can see Eden AI documentation here.

Next step in your project

The Eden AI team can help you with your Topic Extraction integration project. This can be done by :

  • Organizing a product demo and a discussion to understand your needs better. You can book a time slot on this link: Contact
  • By testing the public version of Eden AI for free: however, not all providers are available on this version. Some are only available on the Enterprise version.
  • By benefiting from the support and advice of a team of experts to find the optimal combination of providers according to the specifics of your needs
  • Having the possibility to integrate on a third-party platform: we can quickly develop connectors.

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