The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
We present an automatic approach for discovering location names in WWW data culled from diverse domains. Our approach builds upon the Apache Tika, Apache OpenNLP, and Apache Lucene frameworks. Tika is used to extract text and metadata from any file. The text and metadata are provided to Apache OpenNLP and its location entity extraction model. The discovered location entities are then delivered to...
The effective bandwidth management in multi-service computer networks such as university networks has become a challenge in recent years. The growth of internet traffic and limitation of bandwidth resources persuade the information technology (IT) managers to focus on effective bandwidth allocation policies. One of the important issues discussed in this domain is how to assign the bandwidth fairly...
Most works covering the topic of transfer learning propose an algorithm to solve a given domain adaptation problem, then test the algorithm using real-world datasets. A test with a real-world dataset represents a single transfer learning test condition, which partially measures an algorithm's performance. Previous research has placed little emphasis on developing a comprehensive and uniform test for...
Understanding the sentiment conveyed by a person is a crucial task in any social interaction. Moreover, it can be used to gain insight and understanding of views held by many people. Sentiment classification is not limited to human interaction, as text can also convey the sentiment of the author. Opinion mining in text is a long studied field in machine learning. This study focuses on two of the many...
There is currently a big demand for automating big data analysis. In the data analysis field, data abstraction or summarization playes an important role in the extraction of generalized information from large scale data. We developped an artificial intelligence computer system with the aim of automating big data analysis and came up with a method that can abstract numerical type data (age, height,...
The data streams in many applications are characterized by imbalanced class distribution. The pattern in data streams may also change over time and therefore, the classification model should be adjusted to maintain performance. Hence, a new set of labeled samples should be provided which is not an easy task, since labeling is expensive and time consuming. In this paper, we propose Reduced Labeled...
While cancer treatments are constantly advancing, there is still a real risk of relapse after potentially curative treatments. At the risk of adverse side effects, certain adjuvant treatments can be given to patients that are at high risk of recurrence. The challenge, however, is in finding the best tradeoff between these two extremes. Patients that are given more potent treatments, such as chemotherapy,...
Bagging ensemble techniques have been utilized effectively by practitioners in the field of bioinformatics to alleviate the problem of class imbalance and to improve the performance of classification models. However, many previous works have used bagging only with a single arbitrary number of iterations. In this study, we raise the question of what is the impact of altering the number of iterations/ensembles...
The Internet is a major source of online news content. Current efforts to evaluate online news content, including text, story line and sources is limited by the use of small-scale manual techniques that are time consuming and dependent on human judgments. This article explores the use of machine learning algorithms and mathematical techniques for Internet-scale data mining and semantic discovery of...
A tremendous growth and progress has shown the potential of big data (i.e structured, unstructured and semi-structured) to extract valuable information and do reliable prediction for several industries. Social networking data has created additional opportunities for data scientists and researchers to utilize the data points to advance the predictive and mining models and techniques. However, predictive...
Massive Open Online Courses (MOOCs) are growing substantially in numbers, and also in interest from the educational community. MOOCs are online courses aimed at large-scale interactive participation and open access via the Web that made them possible for anyone with an internet connection to enroll in free, university level courses. In this paper, we propose a novel method to discover various types...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.