Illustrative Results

Phase 1: Data Preprocessing
Phase 2: TFIDF Vector Creation
Phase 3: Input vector Creation
Phase 4: K-Means Clustering of Documents
Phase 5: Topic Terms after LDA Modelling
Phase 6: Semantic Terms
Phase 7: Summarized Documents

Benefits

A summarized document helps in understanding the gist of large text documents quickly and also saves a lot of time by avoiding reading of each individual document in the large text collection. It has a number of real life applications.
  • Analyzing web search results for assisting users in further browsing.
  • Generating summaries for news articles.
  • Generating summaries for legal case reports, etc.
From a user’s perspective, reading newspapers with lots of news content in them can be a tedious and boring task. By summarizing large paragraphs of content into fewer lines without losing the core essence of the content and important detail makes reading less painful.