In recent years, the exponential growth of digital documents has been met by rapid progress in text classification techniques. Newly proposed machine learning algorithms leverage latest advancements deep methods, allowing for automatic extraction expressive features. The swift development these methods led to a plethora strategies encode natural language into machine-interpretable data. modelli...

For the participation of Dublin City University (DCU) in the Relevance Feedback (RF) track of INEX 2010, we investigated the relation between the length of relevant text passages and the number of RF terms. In our experiments, relevant passages are segmented into non-overlapping windows of fixed length which are sorted by similarity with the query. In each retrieval iteration, we extend the cur...

Author profiling is a text classification technique, which is used to predict the profiles of unknown text by analyzing their writing styles. Author profiles are the characteristics of the authors like gender, age, nativity language, country and educational background. The existing approaches for Author Profiling suffered from problems like high dimensionality of features and fail to capture th...

Researchers and scientists need rapid access to text documents such as research papers, source code dissertations. Many are available on the Internet more time retrieve exact based keywords. An efficient classification algorithm for retrieving keyword words is required. The traditional performs less because it never considers words’ polysemy relationship between bag-of-words in To solve above p...