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Clinical summarization means the collection and synthesis of a patient's significant data, undertaken in order to support health-care providers in the process of patient care. Considering that medical information comes from multiple sources, a system for the automatic generation of problem lists could prove to be very effective in terms of saving time in the analysis of large amounts of medical data...
In current times, there has been a surge in the amount of collected data from computational systems. The vast amount of data can be useful in many applications and fields, particularly so in Big Data Analytics. However with a large collection of data there is a difficulty discovering important information. Automatic Document Summarization (ADS) systems are suitable for the task of outlining useful...
Recruiters evaluate and filter job seekers, ranking them on various criteria. This includes how much of the required and desired requirements are satisfied, ensuring the candidate is the “best match” to vacancy. However, most vacancies do not classify the set of skills as required and desired explicitly. Required skills are those skills a job seeker must have in order to be considered for the job...
Traumatic brain injury (TBI) and its complications, including intracranial hypertension, are one of the leading causes of mortality. Many proposed algorithms have attempted to overcome the invasiveness of intracranial pressure monitoring with limited clinical applications. In medical practices, changes of intracranial hypertension are perceived manually, by clinical experts, via surgical placement...
In many websites, data is ubiquitous and contains an abundance of valuable information. As researchers, we often first have to manually extract information from these websites and apply processing techniques to make information structured for further research. In this paper, we propose a smartphone recommendation system based on two websites: www.bestbuy.ca and www.tbaytel.net. The proposed system...
Meeting is a gathering of people to exchange information and plan joint activities for achieving a goal through verbal interactions. In a good meeting, participants' ideas are heard, decisions are made through discussions and activities are focused on desired results. The challenging part is to mine the most relevant interaction pattern from the meeting. Tree structures are not able to capture all...
The opinion mining is very much essential in e-commerce websites, furthermore advantageous with individual. An ever increasing amount of results are stored in the web as well as the amount of people would acquiring items from web are increasing. As a result, the users' reviews or posts are increasing day by day. The reviews toward shipper sites express their feeling. Any organization for example,...
System-call analysis is recognized as one of the most promising approaches to malware detection due to its ability to facilitate detection of malware variants as well as zero-day malware. However, one of the key challenges of system-call based analysis - which prevents it from being used in real-time detection systems - is the excessive size/dimensionality of the system-call sequences that correspond...
Weighted item-set mining is used to find the profitable connection between the data. There are two types of items contained in dataset i.e. frequent and infrequent. Infrequent item-sets are nothing but items which are rarely found in database. Mining frequent items in data mining are very helpful for retrieving the related data present in the dataset. Using transactional dataset as an input dataset...
One of the important approach in data mining is sequential pattern mining that is used for discovering behaviors of sequential databases. There are various challenges in sequential pattern mining such as efficiency and effectiveness. In this paper different sequential pattern mining algorithm are discussed such as GSP, FreeSpan, PrefixSpan, and CAI-PrefixSpan to improve performance to finding sequential...
Inquiry based Inductive learning methodology is one of the best technique especially for the engineering students who are expected to solve real world problems. But it is very difficult to standardize a particular learning methodology for an institution with diverse attitude, diverse characteristics, diverse languages, diverse financial back grounds, and diverse cultural scenario with variable educational...
Thermal convection and fluid flow in porous media has gained increasing research interest in recent years due to the presence of porous media in many engineering applications. Rough set theory has been regarded as a powerful feasible and effective methodology in the performance of data mining and knowledge discovery activities. This paper introduce a method for building knowledge for the rate of heat...
Road accident is one of the crucial areas of research in India. A variety of research has been done on data collected through police records covering a limited portion of highways. The analysis of such data can only reveal information regarding that portion only; but accidents are scattered not only on highways but also on local roads. A different source of road accident data in India is Emergency...
Nowadays, web has become widespread in terms of availability of contents related to every field. Also a large repository of web contents is turned up as a most challenging tool for searching and retrieving information. For scientists and researchers, resource or content searching has been very important. Todays, market is full of variant search tools over web having discrepancy in terms of working...
Since past few years there is tremendous advancement in electronic commerce technology, and the use of credit cards has increased dramatically. As credit card becomes the most popular mode of payment for both online as well as regular purchase, cases of fraud associated with it are also rising. In this paper the authors present the underlying theory of a hybrid model of an Intelligent Fraudulent Detection...
Data mining is one of the most exciting fields of research for the researcher. As data is getting digitized, systems are getting connected and integrated, scope of data generation and analytics has increased exponentially. Today, most of the systems generate non-stationary data of huge, size, volume, occurrence speed, fast changing etc. these kinds of data are called data streams. One of the most...
Multiclass classification is the task of classifying the samples into more than two classes. Generally multi-classifiers face difficulty in classifying samples those are very close to the separating hyperplane, known as Generalization error. Generalization error can be reduced by maximizing the margin of the separating hyperplanes. Support Vector Machine (SVM) is a maximum-margin classifier, its aim...
Sequential pattern mining is valuable approach to uncover consumer buying behaviour from huge sequence database. Weather prediction, web log analysis, stock market analysis, scientific research, sales analysis, and so on are the application of sequential pattern mining. The pattern that is recent and profitable can't discover by conventional sequential pattern mining. So, RFM-based sequential pattern...
The ability to predict one's academic performance is a great asset for both the students and the institution administrators. For the students, they can adjust workload, career direction, etc. If they are aware of their capability. For the administrators and instructors, early warnings would facilitate intervention thus enabling a more successful academic environment. In addition, institutional resources...
Data mining techniques are used to find novel, potentially useful patterns to derive best knowledge from input dataset. For identifying the usefulness of patterns, many constraints have been proposed like time-interval between itemsets, utility parameters (price, profit, quantity etc.), weight of an itemset etc. Time-interval provides interval between consecutive items and utility parameter (profit)...
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