SummarizeBot API AI web data extraction and analysis. Multilingual summarization, keywords and sentiment analysis, multimedia analysis, image and face recognition solutions

SummarizeBot API

AI web data extraction and analysis. Multilingual summarization, keywords and sentiment analysis, multimedia analysis, image and face recognition solutions...


Startup from Latvia
Description

SummarizeBot API provides solutions for text and multimedia analysis. It summarizes automatically, extracts important information, keywords and keyphrases from weblinks, documents, audio files, and images.
With the help of SummarizeBot API you can solve the following tasks:
- Article Summarization: Summarizes an article into a few key sentences. Our summarization and multi-language (100+ languages) algorithm can extract and structure the most important information from text, images and even audio files.
- Sentiment Analysis: Detects sentiment of a document in terms of polarity (positive or negative) and subjectivity (subjective or objective). Our sentiment analysis models are specially trained and optimized for the effective analysis of news articles, while most of our competitors are focused on the analysis of user reviews. Sentiment analysis method supports English, French, German, Italian, Portuguese, Spanish and Russian languages.
- Article Extraction: Extracts the main body of article, including embedded media such as images & videos from an URL and removes all the surrounding clutter. Using our services, you can not only analyze your custom dataset, but also collect your own collection from unstructured sources: extract clean article text and other data from news articles, extract lists of reviews/comments from forums and etc.
- Language Detection: Detects the main language a document is written in and returns it in ISO 639-1 format, from among 60+ different languages.
- Good/Bad News Analysis. Identify what is negative and what is positive in news.
- Comments extraction and video identification.
- Image processing: face detection and object recognition.



Technology

We use the state-of-the-art machine learning algorithms for document format and encoding recognition, text extraction, language detection, sentence/word boundary disambiguation and stemming.
We implement the advanced artificial intelligence classifier which is based on deep linguistic features and used to decrease the redundant information and maximizing the summary relevancy.
We apply Blockchain architecture to train and test our AI models. Using blockchain technology helps us not only to get more training data but also to improve the trustworthiness of our algorithms.


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