Saket S.R. Mengle

One Life. One Aim.

These are the Research Projects that I have been involved in and am working on.

Research Projects

With the ever-increasing number of digital documents, the ability to automatically classifying those documents both quickly and accurately is becoming more critical and difficult. We present Fast Algorithm for Categorizing Text (FACT), which is a statistical based multi-way classifier with our proposed feature selection, Ambiguity Measure (AM), that uses only the most unambiguous keywords to predict the category of a document.

FACT Text classifier

Knowledge of relationships among categories is of the interest in different domains such as text classification, content analysis, and text mining. We propose and evaluate approaches to effectively identify relationships among document categories. Our proposed novel method capitalizes on the misclassification results of a text classifier to identify potential relationships among categories.

Category Relationship Detection

Passages can be hidden within a text to circumvent their disallowed transfer. Such release of compartmentalized information is of concern to all corporate and governmental organization. We present our methodology to detect such hidden passages within a document. A document is divided into passages using various document splitting techniques, and a text classifier is used to classify such passages.

Hidden Passage Detection

Retrieving off-topic documents to a user's pre-defined area of interest via a search engine is potentially a violation of access rights and is a concern to every private, commercial, and governmental organization. We improve content-based off-topic search detection approaches by using a sequence of user queries versus the individual queries.

Misuse Detection