Mita K. Dalal

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Automatic Text Classification is a semi-supervised machine learning task that automatically assigns a given text document to a set of pre-defined categories based on the features extracted from its textual content. This paper attempts to automatically classify the textual entries made by bloggers on various sports blogs, to the appropriate category of sport(More)
In today’s world the volume of information is dramatically increasing, and the value of that information is growing fast. Modern organizations deals with terabytes of text, such as email, that often plays a significant role in their day-to-day operations. Even small and medium-sized organizations are dealing with growing volumes of text that require rapid(More)
Automatic Text Summarization is a specialized text mining task of generating a summary or abstract from single or multiple input text documents. Various heuristic and semi-supervised learning methods have been explored by researchers in this field to generate generic as well as user-oriented summaries. This paper examines the effectiveness of well-known(More)
The complexity of a natural language itself is very challenging as the natural language is not free from ambiguity problem. It is almost impossible to identify that the given text is having sense or not. In today's scenario it becomes even much important to detect that input is given by human or a machine. A valid input with sense is needed everywhere from(More)
Text classification has become one of the major techniques for organizing and managing online information; similarly SMS classification is also an important task now a day. In this paper, we have focused on the issue of short words used in SMS (hpy for happy, bday for birthday) which reduces classification accuracy, so after removing such words with(More)