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An increasing number of Americans use social networking sites such as Facebook, but few fully appreciate the amount of information they share with the world as a result. Although studies exist on the sharing of specific types of information (photos, posts, etc.), one area that has been less explored is how Facebook profiles can share personality information in a broad, machine-readable fashion. In...
This paper utilized sentences containing emoticon from the articles in Yahoo! blogs to automatically detect user's emotions from messenger logs. Four approaches, topical approach, emotional approach, retrieval approach, and lexicon approach, were proposed. Forty emoticon classes found in Yahoo! blog articles were used for experiments. Two experiments were performed. The first experiment classified...
We used a design science approach to explore if a social visualization of the symmetry of relationships existing among members in an online community can motivate participation in terms of reciprocation and responding / commenting to each other's posts. Two different designs are presented: one successful and one that failed to stimulate acts of reciprocation among the users and to increase their level...
Despite the evolution of the hardware that enabled even small components to interconnect and the modern software engineering paradigms that eased information exchange, several systems still operate standalone and do not share resources naturally with each other. In this paper, we show that if these systems are reengineered appropriately using existing techniques, they can share useful resources, work...
In Software Product Line Engineering, where products are derived from a common platform, the reference architecture should be considered the main asset. In order to maintain its correctness and reliability after modifications, a regression testing approach based on architecture specification and code was developed. In this paper, we evaluate it in two different scenarios, the corrective scenario,...
Along with the rapid development of data storing and sharing techniques in terms of both hardware and software, multiple data instances scattered across multiple databases may be available to support one single task, and then making choices of data are necessary from time to time. Research has been conducted on quality or reliability evaluation for individual piece of data assisted by domain knowledge...
The theory which is outlined in this lecture, call it RRC for short, is a departure from traditional approaches to reasoning and computation. A principal advance is an enhanced capability for reasoning and computation in an environment of uncertainty and imprecision. The point of departure in RRC is a basic premise-in the real world such environment is the norm rather than exception.
Welcome to the proceedings of the 13th IEEE International Conference on Information Reuse and Integration (IEEE IRI 2012) in Las Vegas, Nevada, USA. Information Reuse and Integration (IRI) aims at maximizing the reuse of information by creating simple, rich, and reusable knowledge representations and consequently explores strategies for integrating this knowledge into legacy systems. IRI plays a pivotal...
Information integration, interoperability and adaptation to evolving data are the key components of clinical information system with high potential impact. Most existing systems accomplish integration and interoperability by employing specific data model standards with static mapping rules that makes system inflexible and inextensible. In response to this drawback, we present Health-Connect system...
Semantic Web technologies can be utilized to keep patients informed on the latest research on chronic diseases such as diabetes, by gathering online information published by both government and corporate sources. To assemble our Intelligent Health Information System, we created an ontology of terms related to diabetes. Then we leveraged an open-source API to read the ontology into a graphical application,...
This paper uses the Object Oriented Feature Modeling (OOFM) technique to develop Multiple Product Lines (MPLs) and Dynamic SPLs (DSPLs). The idea is combine defined OOFM resources in a Model-View-Controller (MVC) architectural style. As result, a pattern-based Product Line Architecture (PLA) is provided, a kind of middleware that performs an advanced usage of multiple and dynamic OOFM features able...
Long-term (multi-step-ahead) time series prediction is a much more challenging task comparing to the short-term (one-step-ahead) time series prediction. This is due to the increasing uncertainty and the lack of knowledge about the future trend. In this paper, we propose a multi-model integration strategy to 1) generate predicted values using multiple predictive models; and then 2) integrate the predicted...
The quality of a classification model is affected by two factors in a training data set: (1) the presence of excessive features and (2) the presence of imbalanced distributions between two classes in a binary classification problem. This paper presents an iterative feature selection method to deal with these two problems. The proposed method consists of an iterative process of data sampling followed...
Massive amounts of information about news events are published on the Internet every day in online newspapers, blogs, and social network messages. While search engines like Google help retrieve information using keywords, the large volumes of unstructured search results returned by search engines make it hard to track the evolution of an event. A story chain is composed of a set of news articles that...
With the fast development and popularity of digital cameras, smart phones, and video surveillance devices, the amount of video data increases dramatically. Accordingly, automatically mining and annotating high-level concepts for video indexing and management become imperative research tasks in both multimedia research and data mining research. The mainstream content-based semantic concept mining approaches...
kNN is a popular lazy-learning algorithm used for a wide variety of machine learning applications. One problem with this algorithm is the choice of k value. Different k values can have a large impact on the predictive accuracy of the algorithm, and picking a good value is generally unintuitive by looking at the data set. Cross-validation over multiple folds is often used to find the best value for...
Traditional parser evaluation with attachment scores is not helpful for researchers who want to find the most suitable parser for their application. First, because it is being done for a domain which is almost always different from the domain of the application and second because many of the tested dependencies are irrelevant for the application. The alternative extrinsic evaluation is problematic...
This paper presents Rankbox, an adaptive ranking system for mining complex relationships on the Semantic Web. Our objective is to provide an effective ranking method for complex relationship mining, which can 1) automatically personalize ranking results according to user preferences, 2) be continuously improved to more precisely capture user preferences, and 3) hide as many technical details from...
This paper proposes a Bayesian model for multicriteria (MC) recommender systems, which are useful tools for delivering information to those who require it. Such systems usually handle a single overall rating score to capture user's preferences. Recently proposed MC recommender systems use multiple scores evaluated from various aspects to obtain a more elaborate user profile. Our proposed model maps...
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