By using machine learning algorithms, documents can be assigned into different categories, titles, languages or even emotional conditions. In this study we describe our work on creating a distributed classification system for collecting the online news and automatically assigning them to related groups using machine-learning algorithms. II.

Apr 27, 2015 · The goal of this note is to point out that any distributed representation can be turned into a classifier through inversion via Bayes rule. The approach is simple and modular, in that it will work with any language representation whose training can be formulated as optimizing a probability model.

Jan 1, 2015 · In this paper, we propose a supervised framework (Compound RNN) for document classification based on document-level distributed representations learned from deep learning architecture.

Jun 12, 2016 · In the paper we show how these consecutive steps can be realized on the Apache Spark platform dedicated to distributed processing of big data. We illustrate the proposed method by a sample...

We are proposing a simple alternative that turns tted distributed lan- guage representations into document classiers 45. without any additional modeling or estimation.

Document classification is the primary process of retrieving, filtering, clustering and extracting documents. A general procedure for document classification is as follows: First, a set of pre-classified documents is taken as the training set. The training set is then analyzed in order to derive a classification scheme.

In this paper, we propose a new document classification method combining BOW and multiple distributed representations. Different corpus has different words and phrases, so each distributed representation learned from each corpus is expected to have different semantic meaning.

Feb 10, 2018 · We use Apache Big Data technologies such as Hadoop, HDFS, Spark and Mahout, and apply these distributed technologies to Machine Learning. Subjects: Information Retrieval (cs.IR) ; Distributed, Parallel, and Cluster Computing (cs.DC)

We present a distributed documents classification technique using Multi-Agent technology. Naive Bays Classifier is used in a distributed environment for document classification. Experimental results show that the proposed technique is more robust, efficient and effective.

Feb 10, 2018 · Automated text classification has been considered as a vital method to manage and process a vast amount of documents in digital forms that are widespread and continuously increasing.