Text Analytics


Aviant has expertise in Text Mining Framework based on the open source Unstructured Information Management Architecture (UIMA) which acts as a solution accelerator for faster development and delivery of projects related to unstructured textual data.


Aviant’s Text Mining Capabilities


Highlights of the Aviant’s Text Mining Framework :


  • Junk removal from online web articles
  • Automated text classification
  • Information and entity extraction from text using rules and machine learning based systems
  • Discovering domain specific sentiment or opinion words
  • Co-reference resolution and deep Natural Language Processing (NLP)

Statistical Modeling(using SPSS/SAS) 


Organizations need to place voluminous data on a systematic evidence base which requires statistical data analysis. The efficiency of making decisions based on this analysis can be increased by the use of statistical models.

Aviant has developed expertise on SPSS base and SPSS Modeler products over the last 5 years engaging with the SPSS services team. We have worked on few projects from retails, finance and inventory management domains. We have also done predictive modeling in the form of application of regression algorithms, classification and clustering algorithms, time series analysis and forecasting. Aviant also has an experience in developing UI and reporting stuff from SPSS base in connection with interfacing python based modules.


Aviant uses SPSS/SAS to carry out the following tasks:


  • Data preprocessing
  • Exploratory Data Analysis
  • Design and development of Predictive Models
  • Periodic model recalibration