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In nuclear power production, seamless equipment maintenance is integral, significantly achieved through spare parts transactions. Yet, abnormal transaction data can obstruct operational efficiency. Traditional anomaly detection methods, often subjective ...

Massive amounts of data are available for the organization which will influence their business decision. Data collected from the various resources are dirty and this will affect the accuracy of prediction result. Data cleansing offers a better ...

We showcase the first semantic data profiler, DataProf. For the constraint class of interest, current profilers compute all constraints that hold on the given data set. DataProf also computes perfect sample records that together satisfy the same ...

Although the link prediction problem, where missing relation assertions are predicted, has been widely researched, error detection did not receive as much attention. In this paper, we investigate the problem of error detection in relation assertions of ...

We explore in this paper automatic biological sequence type classification for records in biological sequence databases. The sequence type attribute provides important information about the nature of a sequence represented in a record, and is often used ...

In this article, we explore a new mining paradigm, called Indoor Stop-by Patterns (ISP), to discover user stop-by behavior in mall-like indoor environments. The discovery of ISPs enables new marketing collaborations, such as a joint coupon promotion, ...

There is a cultural divide between computer scientists and biologists that needs to be addressed. The two disciplines used to be quite unrelated but many new research areas have arisen from their synergy. We selectively review two multi-disciplinary ...

RFID (Radio Frequency Identification)-based object tracking is increasingly deployed and used in indoor environments such as airports, shopping malls, etc. However, the inherent noise in the raw RFID data makes it difficult to support queries and ...

RFID is widely used for object tracking in indoor environments, e.g., airport baggage tracking. Analyzing RFID data offers insight into the underlying tracking systems as well as the associated business processes. However, the inherent uncertainty in ...

Near duplicate data not only increase the cost of information processing in big data, but also increase decision time. Therefore, detecting and eliminating nearly identical information is vital to enhance overall business decisions. To identify near-...

Poor data quality leads to unreliable results of any kind of data processing and has profound economic impact. Although there are tools to help users with the task of data cleansing, support for dealing with the specifics of time-oriented data is rather ...

One of the motivations for research in data quality is to automatically identify cleansing activities, namely a sequence of actions able to cleanse a dirty dataset, which today are often developed manually by domain-experts. Here we explore the idea ...

Imputation of missing values is an important data mining task for improving the quality of data mining results. The imputation based on similar records is generally more accurate than the imputation based on all records of a data set. Therefore, in this ...

The Radio Frequency Identification (RFID) emerges to be one of the key technologies to modernize object tracking and monitoring systems in indoor environments, e.g., airport baggage tracking. Although RFID has advantages over alternative identification ...

In this tutorial the topic of data preparation for Knowledge Discovery in Databases KDD is discussed on rather general level, with just few detailed descriptions of particular data processing steps. The general ideas are illustrated with application ...

In recent years the Web of Data experiences an extraordinary development: an increasing amount of Linked Data is available on the World Wide Web (WWW) and new use cases are emerging continually. However, the provided data is only valuable if it is ...

We describe a visual data cleansing application for pedigree genotype data, which is used to redeem otherwise unusable pedigree data sets. Biologists and bioinformaticians dynamically and iteratively mask pieces of information from a dirty data set and ...

The human genetic sequence database contains DNA sequences very like those of mycoplasma bacteria. It appears such bacteria infect not only molecular Biology laboratories but their genes were picked up from contaminated samples and inserted into GenBank ...

Data pre-processing plays a vital role in data mining for ensuring good quality of data. In general data pre-processing tasks include imputation of missing values, identification of outliers, smoothening out of noisy data and correction of inconsistent ...