No abstract

Text mining, also known as text analysis, is the process of converting unstructured text data into meaningful and functional information. Text mining uses different AI technologies to automate data and generate valuable insights, allowing enterprises to make data-based decisions. Text mining enables the user to extract important content from text data sets. Text analysis encourages machine learning ability for research areas such as medical and pharmaceutical innovation fields. Apart from this, text analysis converts inaccessible data into a structured format, which can be used for further analysis. Text analysis emphasizes facts and relationships from large data sets. This information is extracted and converted into structured data for visualization, analysis, and integration as structured data and refines the information using machine-learning methods. Like most things related to Natural Language Processing, text mining can seem like a difficult concept to understand. But the fact is, it does not have to be. This research article will go through the basics of text mining, clarify its different methods and techniques, and make it easier to understand how it works. We implemented Latent Dirichlet Allocation techniques for mining the data from the data set; it works properly and will be in future development data mining techniques.

Since it is not possible to be at home and workplace at a single time but it is important to monitor our families and most valuable possessions at home which can be made possible with pervasive technologies. In this paper, we present home alert notifications on mobiles with the help of sensors and wireless cameras so that we can feel free while away from home. A model is proposed in which sensor learns the activity of all persons entering in home and generates alert notifications on administrator's mobile when a person deviates from its normal activity. If an anonymous person comes, he is tracked every time and notifications are generated when he tries to affect any device or lock. The model has the capability to categorize persons on the basis of criteria and decide the functionalities and access available to them in the smart home. It has the facility of monitoring the devices used and generates alerts when any device starts works improperly.