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People's attitude towards specific events is usually contained in their Internet speech. When monitoring public opinions on the Internet, the sentiments of social media users should be analyzed in real time. For example, the expression of target user should be analyzed to get his/her emotional changing trend. However, present literatures on text sentiment analysis are limited to specific domains and...
Multimedia semantic concept detection is an emerging research area in recent years. One of the prominent challenges in multimedia concept detection is data imbalance. In this study, a multimedia data mining framework for interesting concept detection in videos is presented. First, the Minimum Description Length (MDL) discretization algorithm is extended to handle the imbalanced data. Thereafter, a...
Recent developments in social media and cloud storage lead to an exponential growth in the amount of multimedia data, which increases the complexity of managing, storing, indexing, and retrieving information from such big data. Many current content-based concept detection approaches lag from successfully bridging the semantic gap. To solve this problem, a multi-stage random forest framework is proposed...
Precision agriculture is a data-driven farming practice that uses intra-and inter-field information to optimize farming operations. The "brain" of precision agriculture is a decision support system (DSS) that acquires data from various sources, analyzes them, and recommends actions to farmers. Recently cloud computing has been used to improve the scalability and reliability of a DSS. Cloud-based...
A contract is an artifact that records an agreement made by the parties of the contract. Although contracts are considered to be legally binding and can be very complex, they are usually expressed in an informal language that does not have a precise semantics. As a result, it is often not clear what a contract is intended to say. This is particularly true for contracts, like financial derivatives,...
This paper presents a formal method to verify execution time bounds of programs at the source level, where timing constraints along with other functional requirements are specified in the routines' contracts and are verified in a modular manner. The approach works based on a countdown time budget mechanism to guarantee the termination of the input program, and incorporates the concepts of separation...
The lasting popularity of many social Q&A websites, such as Yahoo! Answers and ResearchGate, has become valuable knowledge repositories for people to search for answers to questions in various aspects in life. Finding the most relevant questions is often a non-trivial task, and a fine-grained classification system of questions will be an important aid. Existing work mainly focused on classifying...
The development of distributed systems based on poorly specified abstractions can hinder unambiguous understanding and the creation of common formal analysis methods. In this paper, we outline the design of a system modeling language called DS2, and point out how its primitives are well matched with concerns that naturally arise during distributed system design. We present an operational semantics...
Traditional machine learning requires data to be described by attributes prior to applying a learning algorithm. In text classification tasks, many feature engineering methodologies have been proposed to extract meaningful features, however, no best practice approach has emerged. Traditional methods of feature engineering have inherent limitations due to loss of information and the limits of human...
One of the deficiencies in Z tools is that there is limited support for model checking Z specifications. It is found that building a model checker directly for a Z specification will take considerable effort and time due to an abstraction of the language. Translating a specification input on the Z language into a specification with language that an existing model checker tool accepts is an alternative...
In this investigation, we propose a new method to estimate headlines to news articles. Very often, in news articles, headlines contain characteristic expressions specific to their contents. However, conventional approaches may extract keywords or patterns from article bodies, and put them into well-forms. However we can hardly obtain the characteristic expressions. Here we examine both news articles...
The dissemination of textual personal information has become a key driver for innovation and value creation. However, due to the possible content of sensitive information, this data must be anonymized, which can reduce its usefulness for secondary uses. One of the most used techniques to anonymize data is generalization. However, its effectiveness can be hampered by the Value Generalization Hierarchies...
Mining user reviews to discover what the user likes and dislikes is vital to understanding user behaviors. Topic modeling techniques have been extensively used to discover meaningful topics for user reviews and to discover user behaviors. Extracted topics may be a mixture of different concepts and hence very likely to be less coherent and unclear, especially when extracting a relatively small number...
This paper describes a two-part system that helps developers understand how to search and reuse complex software libraries. First, we present an approach for automatic retrieval of software components in reuse libraries. Second, the system implements a source-code recommendation approach which automatically constructs and delivers relevant code examples that demonstrate how the retrieved components...
Data from computer log files record traces of events involving user activity, applications, system software and network traffic. Logs are usually intended for diagnostic and debugging purposes, but their data can be extremely useful in system audits and forensic investigations. Logs created by intrusion detection systems, web servers, antivirus and anti-malware systems, firewalls and network devices...
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...
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