Dynamic News Classification Using Machine Learning

The big data analytics deals with a large amount of data to work with and also the processing techniques to handle and manage large number of records with many attributes. The combination of big data and computing power with statistical analysis allows the designers to explore new behavioral data throughout the day at various websites. It represents a database that can’t be processed and managed by current data mining techniques due to large size and complexity of data. Big data analytic includes the representation of data in a suitable form and make use of data mining to extract useful information from these large dataset or stream of data. As stated above the big data analytics has recently emerged as a very popular research and practical-oriented framework that implements i) data mining, ii) predictive analysis forecasting, iii) text mining, iv) virtualization, v) optimization, vi) data security, vii) virtualization tools for processing very large data sets. In the implementation of big data applications, new data mining techniques and virtualization are required to be implemented due to the volume, variability, forms and velocity of the data to be processed. A set of machine learning techniques based on statistical analysis and neural networking technology for big data is still evolving but it shows a great potential for solving a big data business problems. Further, a new concept of in-memory database for enhancing the speed for analytic processing is further helping

29) At a very high level, the text mining process consists of each of the following tasks except:

The concepts are the significant advancement in examination and access to quality information. The new aspect of big data that is essential for its application is the variety formats it receive data. The data streams in different format of structured and unstructured (Groves et al., 2016).The data comes in numeric database, videos, audios and email. The data also comes from multiple sources. It is therefore ease to detect the trend and nature of the information in the system. Data management is one of the key aspect of data mining. It involves examination of data and identification based on source and quality (Crockett, & Eliason, 2016). These elements create utility of the information in the system. The health care will therefore get quality information for improving its

Xiang, Z., Schwartz, Z., Gerdes, J. H., & Uysal, M. (2015). What can big data and text

I have analyzed three online news publications from different parts of the world. Those are Fox News from the U.S., BBC from England and Mail & Guardian from South Africa. In this research paper I will present quantitative research that indicates the statistically significance between them.

Classify - Classification allows clinicians and researchers to describe disorders, predict outcomes, suggest treatments, and encourage research. Psychologists use a reference book called the Diagnostic and Statistical Manual of Mental Disorders (DSM) to diagnose psychological disorders. The DSM-IV uses a multi-axial system of classification, which means that diagnoses are made on several different dimensions. There are many mental illnesses, however, when it

The author points out that although there are existing algorithms and tools available to handle Big Data, they are not sufficient as the volume of data is exponentially increasing every day. To show the usefulness of Big Data mining, the author highlighted the work done by United Nations. In order to further enhance the reader’s perspective, the author provided research work of various professionals to educate its readers about the most recent updates in Big Data mining field. The author further describes the controversies surrounding Big Data. The author has first provided the context and exigence by elaborating on why we need new algorithm and tools to explore the Big Data. The author used the strategy of highlighting the logos by mentioning the research work of different industry professionals, workshops conducted on Big Data and was able to appeal to connect to the reader’s ethos. The author also used pathos by urging the budding Big Data researchers to further dig deep into the topic and explore this area

Text mining is generally identical to content examination it is the way toward getting brilliant data from text. Fantastic data is ordinarily determined through the concocting of examples and patterns through means, for example, factual example learning. Content mining as a rule includes the way toward organizing the information message typically parsing, alongside the expansion of some determined phonetic highlights and the expulsion of others, and ensuing inclusion into a database, inferring designs inside the organized information, lastly assessment and elucidation of the yield. 'High caliber' in content mining more often than not alludes to some blend of pertinence, oddity, and interesting .Text examination programming can help by transposing words and expressions in unstructured information into numerical esteems which would then be able to be connected with organized information in a database and broke down with conventional information mining techniques. Text mining is a minor departure from a field called information mining that tries to discover

The main purpose is to detect topics automatically and track related documents from a stream of documents temporally so that readers can understand. First stage, Theme Generation process tries to identify the theme of the topic. Next Event Segmentation and Summarization models the documents as a symmetric block association matrix. Eigen vectors are then drawn to examine and extract summaries. Finally, Temporal Similarity (TS) function is used to calculate the event dependencies. This had given me an opportunity to expose my knowledge in Software Engineering and Data Mining. This also helped us to gain domain knowledge and also enhance technical skills like Servlets and JSP, used for implementing main logic, while JDBC for back end database connection and performing basic operations of database and Html for UI

Data classification is the process of organizing data into categories for the most effective and efficient use. A well-constructed data classification system is a staple of any data loss prevention policy because it

The result that an institution receives from the Savitribai Phule Pune University (SPPU) is in PDF (Portable Document File) format file. To analyze and manipulate them manually is very tedious job for a person. This is where text mining and file format convertors come into light to overcome this kind of problem. Text mining has an exceptional contribution for programmers and scientists to mine data out from textual files. Text mining overlooks the redundant textual data and only targets only on the required data patterns. Text mining plays important role because its center of functioning is devising patterns into necessary format or could be said that it derives a very quality of information from text. File format conversion has always been a bridge as well as challenge to access that particular data without particular tool. Different files have protocol set like internal and

Information Technology has revolutionised the way through which people access information. Chen’s article, “Newspapers fold as readers defect and economy sours” shows this by detailing the collapse of the newspaper industry and its replacement by online news. Prior to the widespread availability of the internet, consumers were forced to rely on newspapers and television to find out the news of the world. These comparatively old medias are offered to the public on a delay due to the process of printing and production. However, the internet now offers news and information to these same people, free of charge and on demand.

Data Classification is the process of categorizing data into different groups or classes for effecting management. It is very essential for organization to classify data as it allows them to determine the degree of sensitivity and criticality of each class of data and as a result, appropriate level of protection can be applied based on the assigned sensitivity level. Over or under protection of data can be avoided with proper data classification as only the necessary level of

bitts.beans@gmail.com ABSTRACT In this paper we are going to illustrate a way to cluster similar news articles based on their term frequency. We will using python and nltk to recognize keywords and subsequently using hierarchical clustering algorithm. This method can be used to build news aggregation backends. Aggregation means clustering like documents from different sources.

The target user group for the news system I am designing is the people who care about the technology news. For example, the person studying Computer Science at the university wants to know the latest technology. Not only the students, but also other people who are fans of technology as they have the specific requirement in the technology field. Since most of the elder people are not interested in this field and are used to reading newspaper rather than using mobile, they are not the main target user group. In view of a small part of them, they are not excluded. However, the news system I am designing does not specifically focus on feature for the elder people.