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Post Traumatic Stress Disorder (PTSD) is a public health problem afflicting millions of people each year. It is especially prominent among military veterans. Understanding the language, attitudes, and topics associated with PTSD presents an important and challenging problem. Based on their expertise, mental health professionals have constructed a formal definition of PTSD. However, even the most assiduous...
An ontology is a framework for describing domain-specific knowledge in a structured format. It is comprised of a set of terms as nodes and a set of relationships between terms as directed edges to form a directed acyclic graph. Gene Ontology (GO) and Human Phenotype Ontology (HPO) are widely referred biological and biomedical ontology databases. They also provide extensive annotations of human genes...
TCM is a traditional medicine in China and has made great contributions to the Chinese nation and has rich information resources. With the development of information technology, data mining technology is rapidly rising. Under the guidance of Chinese medicine theory, how to combine data mining technology with Chinese medicine to make it serve people has become a new topic. This paper mainly applies...
Blast furnace (BF) ironmaking process is a typical complex nonlinear industrial process. Aiming at the problem that the relationship between the operating parameters and the main production indicators in BF ironmaking process mainly depends on the subjective experience of the specialized operators and experts, and is difficult to be inherited and studied later, this paper introduces data mining technology...
In this paper, we formally prove that the classification rules formed on the basis of contrast patterns are guaranteed to be of a high quality. We propose to use the new ‘Sets of Contrasting Rules’ pattern for the identification of local differences between the classes of the dataset. Being essentially a contrast pattern formed of several classification rules, ‘Sets of Contrasting Rules’ pattern is...
Nowadays, increasing data sizes have grown at incredible levels. Many firms want to interpret their produced data and reach the useful information. In this study, by making customer basket analysis of a company operating in the retail sector, to organize suitable campaigns for the customers has been aimed and sales amounts of campaign items have been predicted before the campaign. The association...
One of the most classic algorithms for association rules mining is the Apriori algorithm. But it can't satisfy the requirement as the increasing scale of the data. It has some disadvantages such as scanning database too many times, setting support and confidence thresholds artificially. Particle swarm optimization is one of the classic heuristic algorithms and some researchers has used it to association...
No Evidence of Disease (NED) is breast cancer patient condition status which it indicates that they can life, no find the cancer by tested, and without any symptoms of cancer in period of times, after they received primary treatment. NED is a critical status, because it involves the treatment type and patient cancer condition factors. This paper examines about breast cancer problem in data mining...
The purpose of this paper is to identify vehicle driver injury severity factors of highway-railway grade crossing (HRGC) accidents in order to detect interactions as well as dissimilarities among accident factors. At this aim, data mining techniques were used to analyze the interaction of multiple factors in large databases. This paper applies Classification-Regression Tree (CART) and Association...
We consider a special case in association rule mining where mining is conducted by a third party over data located at a central location that is updated from several source locations. The data at the central location is at rest while that flowing in through source locations is in motion. We impose some limitations on the source locations, so that the central target location tracks and privatizes changes...
In this paper, we present a method to extract the possible relationships between knowledge points by analyzing e-book log and mining quiz data and mining Wikipedia articles. This method will be implemented in an ontology-based visualization support system to support the instructor to construct course-centered ontologies semi-automatically.
Computer software size continues to grow recently. But it is difficult to collect information to support software development and maintenances. Data mining technology can be used to automatically discover knowledge from software testing data. It is helpful to increase software developing process and improve software quality. At first, correlation analysis is adopted to study the relevance among the...
Data mining can find some interest information from large amounts of data. Data association (association rules) can find associations among data items. Data classification distinguishes every data from a data set or group, and it also can combine data association. Formal concept analysis is a data analyzing theory which discovers concept structure in data sets. It can transform formal context into...
With complex pathogenesis, Chronic Obstructive Pulmonary Disease (COPD) is difficult to treat. Traditional Chinese Medicine (TCM) showed obvious effect in treating COPD. However, invaluable TCM experience lacks of systematic summarization and study. Association rule is used to discover the relationships among data items in a large amount of data. Because of clear and useful results, association rule...
Ubiquitous connectivity and smart technologies gradually transform homes into Intranet of Things, where a multitude of connected, intelligent devices allow for novel home automation services. Providing new services for home users (e.g., energy saving automations) and Internet Service Providers (e.g., network management and troubleshooting) requires an in-depth analysis of various kinds of data (connectivity,...
This study performs an Affinity Analysis ondiagnosis and prescription data in order to discover cooccurrencerelationships among diagnosis and pharmaceuticalactive ingredients prescribed to different patient groups. Theanalysis data collected during consecutive visits of 4,473 patients in a 3 years period, focused on patients suffering byhypertension and/or hypercholesterolemia and appliedassociation...
Association and sequential rules have received much attention in both academia and in practice for quite some time. A number of algorithms have been proposed to improve the efficiency of mining decision rules. However, these centralized algorithms have been criticized for their inapplicability to distributed environments. Although many sophisticated distributed algorithms for mining association and...
For a large sum of data collected and stored continually, it is more and more necessary to mine association rules from database, and the Apriori algorithm of association rules mining is the most classical algorithm of database mining and is widely used. However, Apriori algorithm has some disadvantages such as low efficiency of candidate item sets and scanning data frequently. Support and confidence...
During the status of real-time flight monitoring, it is related to the safety of flight that the accuracy of engine's rub-impact failure detection under the strong vibration environments. Under the strong vibration environment, when engine goes to stationary state, the engine's rub-impact failure is easy to happen, and they are often happened simultaneously. However, there is no correlation between...
With the advent of the big data era, data mining technology has gradually become mature, association rules analysis is also applied in many fields. Web log mining is an important way to do some personalized services and achieve Web personalize. Apriori algorithm is a classical algorithm of association rules, but it has a lot of shortcomings. In recent years, the improvement about Apriori algorithm...
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