Rajendra Sharma's Blog / Share Your Thoughts
  • C-value approach to multi-word automatic term recognition (ATR)

    By: Rajendra Sharma | July 29, 2015

    C-value is a domain-independent method for multi-word ATR which aims to increase the extraction of nested terms. It aims to get more accurate terms, especially those nested terms, such as ”MUTUAL INFORMATION” nested in longer

  • Image metadata

    By: Rajendra Sharma | June 26, 2015

      Metadata may be written into a digital photo file that will identify owner of it, copyright and contact information, what camera created the file, along with exposure information and descriptive information such as keywords

  • LIRE: Lucene Image Retrieval

    By: Rajendra Sharma | June 19, 2015

      LIRE is a Java library that provides a simple way to retrieve images based on their colours and texture features. LIRE creates a Lucene index of image features for content based image retrieval (CBIR).

  • Image Processing and Analysis in R

    By: Rajendra Sharma | June 12, 2015

    Performing Image processing and analysis in R, installation of EBImage package is required. Execute the below code to get package installed in R. Performing the Reading, Writing and displaying of Image The loading of package

  • Supervised Learning for Text Classification

    By: Rajendra Sharma | May 28, 2015

    Text Classification (or Categorization) has been investigated by many researchers over more than past 2 decades. Due to the extreme increase in online textual information, e.g. Email messages, online news, web pages, as well as

  • k-means clustering

    By: Rajendra Sharma | May 15, 2015

    What is Clustering? Clustering is the process of partitioning a group of data points into a small number of clusters. K-means Clustering K-means clustering (MacQueen, 1967) is a method commonly used to automatically partition a

  • Word Cloud in R

    By: Rajendra Sharma | April 24, 2015

    Word Cloud A word cloud is a graphical representation of frequently used words in a collection of text data. The height of each word in the visualization is an indication of frequency word in the