Discover Insights from Vast Textual Data

Discover Insights from vast textual data

We use Entity Recognition to find main themes, topics and entities. 

Visualize the textual territory

We use machine learning algorithms to discover main topics to create navigation tools through 3D landscape across large volume of scattered textual data. With VizRefra, we offer Text Analysis, unique ML algorithms, topic modeling with navigation through 2D/ 3D maps, as well as sentiment analysis, word cloud and entity recognition 

Visualize the textual territory

Visualize the textual - Textual Data Analysis

Relate to learn Textual Data Analysis

Create relationship with our sate of the art Python customized programs to find hidden relationships in the text.

Twitter or Facebook, we got you covered:

Monitor social media to learn about your customers and trends related to your products or your organization reputation. 

Information visualizing is an emerging and challenging area of research due to its unstructured nature and potential impact. Visualization of data provides instant understanding and facilitates effective communication medium.

 

The rapid increase in information and unstructured data creates a challenge in gauging particular data availability in a selected field. For example, considering the rapid development on the information related to Covid-19 disease symptoms, possible treatments, vaccine development and tons of research papers developed, to find information about the latest analysis on transmission method for example, you will plan to conduct a full research project to locate these development ensued in that field, in some situations you will end up creating many categorical levels for different datasets collected despite the great by global organizations to sort these papers, the massive number of papers published daily since the spread of the disease is been.

 

Looking at Cholera disease for which countries that are impacted in the last 20 years, for example, is going to be not only a very difficult task, but tedious quest when trying to locate quantitative or qualitative data. In Figure 1, there is an average of 20,000 publications a year, each has a minimum of 6000 words, and the researcher is only left with search word-by-word to find particular details of interest. Often re- searchers will face many challenges when attempting to locate data and information due to the massive data availability with less structured categories.

It is no  surprise that there are many different attempts to design    a suitable text visualization tool to help find and navigate through  the information universe more efficiently

 

vizrefra.com uses a unique approach to visualization by providing a real human created tags predicting topics used in text you want to analyze. The solution provides 2D text mapping and 3D map to navigate through text. The engine learns about the text you like to analyze to produce related topics that are already published.