Background & Aims: Diabetes mellitus is one of the most common types of chronic disease leading to serious complications such as blindness, end stage renal disease (ESRD), neuropathy and cardiac disorders. Skin tag is a common benign skin tumor that its association with impaired carbohydrate metabolism has been reported in some studies. The aim of this study was to compare the frequency of diab...

This paper describes an approach to fraud detection targeted at applications where this task is followed by a posterior human analysis of the signaled frauds. This is a frequent setup on fraud detection applications (e.g. credit card misuse, telecom fraud, etc.). In real world applications this human inspection is usually constrained by limited resources. In this context, standard fraud detecti...

The analysis of the large volume of tandem mass spectrometry (MS/MS) proteomics data that is generated these days relies on automated algorithms that identify peptides from their mass spectra. An essential component of these algorithms is the scoring function used to evaluate the quality of peptide-spectrum matches (PSMs). In this paper, we present new approach to scoring of PSMs. We argue that...

Clustering is a data mining (machine learning) technique used to place data elements into related groups without advance knowledge of the group definitions. Data Extraction is the process of retrieving data out of data sources. Establishment of an updated method called a novel data extraction and alignment method called CTVS that combines both tag and value similarity enhances the efficiency of...

Searching for services often starts from the exploration of the service space. Community generated tags can support such exploration. Researchers attracted by the community-available “free manpower” proposed more complex tagging models. Those models tag specific parts of the Web service definition: single operations, their inputs and outputs. However, there is no evidence whether the annotation...

The tagged and nested structure of an XML document provides quite detailed information about its structure and semantic, which is neglected by traditional keyword search model like TF-IDF and BM25 etc. Popular XML search models such as SLCA and XRANK tend to return the “deepest” node containing all given keywords, which usually leads to semantic loss. In this paper, we introduce the concept of ...