Una aproximación a la predicción del valor de acciones en la bolsa de valores aplicando técnicas de Data Mining

La predicción del valor de las acciones en la bolsa de valores ha sido un tema importante en el campo de inversiones, que por varios años ha atraído tanto a académicos como a inversionistas. Esto supone que la información disponible en el pasado de la compañía que cotiza en bolsa tiene alguna implicación en el futuro del valor de la misma. Este trabajo está enfocado en ayudar a un persona u organismo que decida invertir en la bolsa de valores a través de gestión de compra o venta de acciones de una compañía a tomar decisiones respecto al tiempo de comprar o vender basado en el conocimiento obtenido de los valores históricos de las acciones de una compañía en la bolsa de valores. Esta decisión será inferida a partir de un modelo de regresión múltiple que es una de las técnicas de datamining. Para llevar conseguir esto se emplea una metodología conocida como CRISP-DM aplicada a los datos históricos de la compañía con mayor valor actual del NASDAQ.---ABSTRACT---The prediction of the value of shares in the stock market has been a major issue in the field of investments, which for several years has attracted both academics and investors. This means that the information available in the company last traded have any involvement in the future of the value of it. This work is focused on helping an investor decides to invest in the stock market through management buy or sell shares of a company to make decisions with respect to time to buy or sell based on the knowledge gained from the historic values of the shares of a company in the stock market. This decision will be inferred from a multiple regression model which is one of the techniques of data mining. To get this out a methodology known as CRISP-DM applied to historical data of the company with the highest current value of NASDAQ is used.

Mining mobile apps reviews to support release planning

The mobile apps market is a tremendous success, with millions of apps downloaded and used every day by users spread all around the world. For apps’ developers, having their apps published on one of the major app stores (e.g. Google Play market) is just the beginning of the apps lifecycle. Indeed, in order to successfully compete with the other apps in the market, an app has to be updated frequently by adding new attractive features and by fixing existing bugs. Clearly, any developer interested in increasing the success of her app should try to implement features desired by the app’s users and to fix bugs affecting the user experience of many of them. A precious source of information to decide how to collect users’ opinions and wishes is represented by the reviews left by users on the store from which they downloaded the app. However, to exploit such information the app’s developer should manually read each user review and verify if it contains useful information (e.g. suggestions for new features). This is something not doable if the app receives hundreds of reviews per day, as happens for the very popular apps on the market. In this work, our aim is to provide support to mobile apps developers by proposing a novel approach exploiting data mining, natural language processing, machine learning, and clustering techniques in order to classify the user reviews on the basis of the information they contain (e.g. useless, suggestion for new features, bugs reporting). Such an approach has been empirically evaluated and made available in a web-­‐based tool publicly available to all apps’ developers. The achieved results showed that the developed tool: (i) is able to correctly categorise user reviews on the basis of their content (e.g. isolating those reporting bugs) with 78% of accuracy, (ii) produces clusters of reviews (e.g. groups together reviews indicating exactly the same bug to be fixed) that are meaningful from a developer’s point-­‐of-­‐view, and (iii) is considered useful by a software company working in the mobile apps’ development market.

Practical coal-mining,

Mode of access: Internet.

A dictionary of Spanish and Spanish-American mining, metallurgical and allied terms, to whichs some Porutguese and Portuguese-American (Brazilian) terms are added,

"List of principal works consulted": p. vii-[ix]

The Merrill story : (being a record of the life and achievements of Charles Washington Merrill, and a history of the Merrill Company and subsidiaries) /

Mode of access: Internet.

Prospectus of the West Virginia Iron Mining and Manufacturing Co., incorporated by the Legislature of Virginia, Mar. 15, 1837.

Mode of access: Internet.

A brief description of the property belonging to the Lycoming Coal Company : with some general remarks on the subject of the coal and iron business.

"Dec. 1828."

High grade engineering, surveying and mining instruments /

Mode of access: Internet.

A text-book of coal-mining. For the use of colliery managers and others.

Short bibliography at end of each chapter.

Two reports: on the coal lands, mines and improvements of the Dauphin and Susquehanna coal company, and of the geological examinations, present condition and prospects of the Stony Creek coal estate, in the townships of Jackson, Rush, and Middle Paxtang, in the country of Dauphin, and of East Hanover township,

Mode of access: Internet.

The Mining world index of current literature

Subtitle varies slightly

Leaves from an Argonaut's note book; a collection of holiday and other stories illustrative of the brighter side of mining life in pioneer days

The milk pan.-The new leaf.-The Thanksgiving dinner.-The reservoirs.-The legend of Humbug Gulch.-The Joes.-Cyrus Billings' dream.-Bill's luck.-The ferry.-Simpson's Thanksgiving.-Stubbs' wooing.-The end of leap year.-Mrs. Crumpey's boarders.-Mr. Snively's vacation.-The story he told the prospectors.

Company E., Iron Mountain Volunteers in the Spanish-American War

verso: taken 1898 at Central House, old hotel in Iron Mountain, meeting place for mining men, etc.

Roughing it in Siberia, with some account of the Trans-Siberian railway, and the gold-mining industry of Asiatic Russia,

Mode of access: Internet.

Mineral land surveying : a technical treatise on the surveying and patenting of mineral land, designed for the use of Deputy Mineral Surveyors and Students of Mining Engineering, with an appendix of contributed notes of interest /

Reprint. Originally published: Denver : The Mining Reporter Publishing Company, 1906.