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features
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support

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Description

Athens is an innovative, open-source platform designed for tech enthusiasts. It allows users to dynamically create, link, and enhance their research and documentation through a collaborative knowledge graph. Engage with over 2,500 individuals who share a passion for learning, explore new research methodologies, and contribute to shaping the future of self-hosted knowledge graphs. In today's fast-paced world, we often find ourselves overwhelmed by information overload. While note-taking is essential to retain knowledge, the sheer volume of notes can become unmanageable. Traditional search functionalities often fall short, folder systems can be cumbersome, and tagging is frequently overlooked. Athens revolutionizes note-taking by eliminating the reliance on inefficient search methods, the frustration of navigating complex folders, and the hassle of manual tagging. Athens Research fosters a remote learning community dedicated to creating a powerful, transparent, and open-source knowledge repository; this endeavor culminates in Athens, a free knowledge graph tailored for research and note-taking. Built on principles of openness, privacy, extensibility, and community engagement, Athens provides users with a unique platform to enhance their knowledge-sharing experience. Ultimately, Athens empowers individuals to streamline their note-taking processes while fostering collaboration and innovation.

Description

At Iris.ai we have spent the last 6 years building an award-winning AI engine for scientific text understanding. Our algorithms for text similarity, tabular data extraction, domain-specific entity representation learning and entity disambiguation and linking measure up to the best in the world. On top of that, our machine builds a comprehensive knowledge graph containing all entities and their linkages to allow humans to learn from it, use it and also give feedback to the system. The Iris.ai Researcher Workspace is a flexible tool suite that allows to approach a project in a variety of ways. Modules include content based explorative search, machine analysis of document sets, extracting and systematizing data points, automatically writing summaries of multiple documents - and very powerful filters based on context descriptions, the machine’s analysis, or specific data points or entities. The Iris.ai engine for scientific text understanding is a powerful interdisciplinary system that can be automatically reinforced on a specific research field for much more nuanced machine understanding - without human training or annotation.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Advantage

Integrations

Advantage

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Athens

Website

www.athensresearch.org

Vendor Details

Company Name

Iris.ai

Founded

2015

Country

Norway

Website

iris.ai/

Product Features

Idea Management

Activity Dashboard
Brainstorming
Collaboration
Creator Tracking
Idea Ranking
Project Tracking
Status Tracking

Product Features

Data Extraction

Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

Qualitative Data Analysis

Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Quantitative Content Analysis
Sentiment Analysis
Statistical Analysis
Text Analytics
User Research Analysis

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