Abstract— Feature selection is a term commonly used in data mining to describe the tools and techniques available for reducing inputs to a manageable size for processing and analysis. Feature selection implies not only cardinality reduction, which means imposing an arbitrary or predefined cutoff on the number of attributes that can be considered when building a model, but also the choice of att...

Polarity detection of Online Reviews is one of the most popular tasks related to Opinion Mining. Given that most state-of-the-art solutions ignore the structural aspects of a review, we present an approach to polarity detection that, first, distinguishes stages in the genre of hotel reviews and, subsequently, evaluates the usefulness of each type of stage in the determination of the polarity of...

The explosive growth of spatial data and widespread use of spatial databases emphasize the need for the automated discovery of spatial knowledge. Spatial data mining is the process of discovering interesting and previously unknown, but potentially useful patterns from spatial databases. The complexity of spatial data and intrinsic spatial relationships limits the usefulness of conventional data...

As far as this author is aware this is the rst paper to de scribe the application of Progol to enantioseparations A scheme is pro posed for data mining a relational database of published enantiosepar ations using Progol The application of the scheme is described and a preliminary assessment of the usefulness of the resulting generalisations is made using their accuracy size ease of interpretati...

Association rule mining (ARM) is the process of generating rules based on the correlation between the set of items that the customers purchase.Of late, data mining researchers have improved upon the quality of association rule mining for business development by incorporating factors like value (utility), quantity of items sold (weight) and profit. The rules mined without considering utility val...

Faculty of Science School of Computing Sciences Doctor of Philosophy by Khaled S. Alotaibi Recent advances in the field of data mining have led to major concerns about privacy. Sharing data with external parties for analysis puts private information at risk. The original data are often perturbed before external release to protect private information. However, data perturbation can decrease the ...

Generally, association rule mining uses only a single minimum support threshold for the whole database. This model implicitly assumes that all items in the database have the same nature. In real applications, however, each item can have different nature such as medical datasets which contain information of both diseases and symptoms or status related to the diseases. Therefore, association rule...

Although support has been used as a fundamental measure to determine the statistical importance of an itemset, it can’t express other richer information such as quantity sold, unit profit, or other numerical attributes. To overcome the shortcoming, utility is used to measure the semantic importance and several algorithms for utility mining have been proposed. However, existing algorithms for ut...