The paper investigates the problem of sentence readability assessment, which is modelled as a classification task, with a specific view to text simplification. In particular, it addresses two open issues connected with it, i.e. the corpora to be used for training, and the identification of the most effective features to determine sentence readability. An existing readability assessment tool dev...

Text clustering and classification are two main tasks of text mining. Feature selection plays the key role in the quality of the clustering and classification results. Although word-based features such as term frequency-inverse document frequency (TF-IDF) vectors have been widely used in different applications, their shortcoming in capturing semantic concepts of text motivated researches to use...

In the present world of information, text classification is a more challenging process due to the larger number of training cases and feature set present in text data. One of the most difficult tasks in the text classification problem is high dimensionality of the feature space. As many real world text classifications are not modeled or too difficult to model, this paper aims at the real world ...

Huge amount data on the internet are in unstructured texts can‟t simply be used for further processing by computer , therefore specific processing method and algorithm require to extract useful pattern. Text mining is process to extract information from the unstructured data. Text classification is task of automatically sorting set of document into categories from predefined set. A major diffic...

We present novel method for image-text multi-modal representation learning. In our knowledge, this work is the first approach of applying adversarial learning concept to multi-modal learning and not exploiting image-text pair information to learn multi-modal feature. We only use category information in contrast with most previous methods using image-text pair information for multi-modal embeddi...

The main objective is to propose a text classification based on the features selection and preprocessing thereby reducing the dimensionality of the Feature vector and increase the classification accuracy. Text classification is the process of assigning a document to one or more target categories, based on its contents. In the proposed method, machine learning methods for text classification is ...

Problem statement: Text documents are the unstructured databases that contain raw data collection. The clustering techniques are used group up the text documents with reference to its similarity. Approach: The feature selection techniques were used to improve the efficiency and accuracy of clustering process. The feature selection was done by eliminate the redundant and irrelevant items from th...

today a significant part of available data is saved in text database or text documents. the most important thing is to organize these documents. one way to organize text documents is to classify them. to classify texts is to assign text documents to their actual categories. this has two main steps, i.e. feature- and learning algorithm selection. there have been several methods suggested to clas...