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Crime analysis is a methodical approach for identifying and analyzing patterns and trends in crime. With the increasing origin of computerized systems, crime data analysts can help the Law enforcement officers to speed up the process of solving crimes. Using the concept of data mining, we can analyze previously unknown, useful information from an unstructured data. Predictive policing means, using...
Credit risk is related to the risk of the borrower that the lender will not be able to return their debt including interest. Numerous researches have been conducted in the area of credit risk, both using classical models such as Altman Z-score and using machine learning methodology. However, the research using the data from Croatian financial institutions is scarce, especially research focused on...
In this paper, we present an application designed to analyze news articles from Romanian mass media and extract opinions about political entities relevant to the major political stage. The application was created with the desire to study media polarization around important political events, such as legislative or presidential elections. The application uses different crawlers to extract the data from...
For the modeling problem of microbial fermentation process, taking glutamic acid fermentation process as the research object, the decision tree and the random forest model were established by using the data mining method, and the model was evaluated and predicted by using the R language. Good effect of the decision tree model, indicating that the decision tree package of R language has a certain flexibility,...
The table-organized data can be analyzed by various algorithms; some of them are capable of generating IF THEN decision rules which comprises of condition attributes and decision attributes. However, it is possible to reduce the set of condition attributes but without information loss. By analysis of the condition attributes set and cuts histogram obtained by discretization and rule consistency, it...
This paper discusses the application and benefits of data mining techniques to construct prediction models in the field of corporate bankruptcy. It analyzes a dataset of 120 companies using different data mining techniques. Findings show that neural network is recommended as the best model to predict corporate bankruptcy. Findings also show that the proper use and selection of data mining techniques...
Nowadays, along with the development of information technologies, storage and analysis of biomedical datasets are easy in health sector. In this area, Machine Learning methods provide a great contribution for evaluation and interpretation of data. In this paper, in addition to Support Vector Machines, Decision Tree, K-Nearest Neighbors, Naive Bayes and Dictionary Learning methods, Random Feature Subspaces...
Extracting opinion words and product features is an important task in many sentiment analysis applications. Opinion lexicon also plays a very important role because it is very useful for a wide range of tasks. Although there are several opinion lexicons available, it is hard to maintain a universal opinion lexicon to cover all domains. So, it is necessary to expand a known opinion lexicon that are...
Titanic disaster occurred 100 years ago on April 15, 1912, killing about 1500 passengers and crew members. The fateful incident still compel the researchers and analysts to understand what can have led to the survival of some passengers and demise of the others. With the use of machine learning methods and a dataset consisting of 891 rows in the train set and 418 rows in the test set, the research...
Education can be utilized as a tool to face many problems, overcome many hurdles in life. The knowledge obtained from education helps to enhance opportunities in one's employment development. To extract useful information from the knowledge obtained, Educational Data Mining is widely used. Educational data mining provides the process of applying different data mining tools and techniques to analyze...
The fast development of wireless sensor networks has made a chance to accumulate and remove enormous measure of data from Wireless Sensor Networks. WSN is efficient instrument that empowers its clients to nearly screen, comprehend and control application handle. WSN consist of huge number of heterogeneous sensor hub spread over the extensive territory and help for wireless sensing and data processing...
Machine learning and Data mining techniques are rapidly establishing themselves in medical and health care fields. This paper addresses a similar issue where the fitness of an individual can be predicted by analyzing few attributes associated with that individual. A hybrid classifier algorithm is developed by merging Decision Tree and Naïve Bayes algorithms which will classify the Fitness data set...
Classification is a central problem in the fields of data mining and machine learning. Using a training set of labeled instances, the task is to build a model (classifier) that can be used to predict the class of new unlabelled instances. Data preparation is crucial to the data mining process, and its focus is to improve the fitness of the training data for the learning algorithms to produce more...
Stream mining is a trending field of research in this digital age. With the increase in number of users of digital technologies, data is generating exponentially and so is the need to analyse it. This data is very huge in size and cannot be kept stored for a long time, so it must be processed as soon as possible to make space for newly arriving data & to achieve this different single scan algorithms...
With the rapid growth of web technology there is a huge amount of data present in the web for internet users. Such data is mainly from the social media such as Facebook [4], twitter, etc., where millions of people express their views in their daily interaction which can be their sentiments or opinions about a particular thing. Large amount of data also present in the forms of reviews and ratings in...
Users of search engines interact with the system using different size and type of queries. Current search engines perform well with keyword queries but are not for verbose queries which are too long, detailed, or are expressed in more words than are needed. The detection of verbose queries may help search engines to get pertinent results. To accomplish this goal it is important to make some appropriate...
We don't have a choice on whether we DO social media, the question is how well we DO it. To track the mood of people about any particular product by review we use opinion mining which is a natural language processing technique. Customer review analysis is most important only by which product is rated and it is a major problem today. Reviews from social media are collected manually and then pre-processed...
Color transfer techniques have been widely developed to manipulate color information of image data in many applications. In this paper, color transfer research is presented for camouflage applications, along with the challenges facing many state-of-the-art color transfer methods. To address these challenges, a new fast color transfer algorithm is proposed. This new fast color transfer algorithm follows...
Data mining is an advanced technology, which is the process of discovering actionable information from large set of data, which is used to analyze large volumes of data and extracts patterns that can be converted to useful knowledge. Medical data mining has a great potential for exploring the hidden patterns in the data sets of medical domain. These patterns can be utilized to do clinical diagnosis...
In technical graduate courses like engineering, it is very important that students are monitored during their first year. It is important for all technical graduates to have a good programming insight. Still, a student shying away from the core subjects like programming is common phenomena in engineering colleges nowadays. It is thus necessary to keep track of students' performance during the first...
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