Kostyantyn M. Shchekotykhin

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The effective debugging of ontologies is an important prerequisite for their successful application and impact on the semantic web. The heart of this debugging process is the diagnosis of faulty knowledge bases. In this paper we define general concepts for the diagnosis of ontologies. Based on these concepts , we provide correct and complete algorithms for(More)
The complexity of product assortments offered by e-Commerce platforms requires intelligent sales assistance systems alleviating the retrieval of solutions fitting to the wishes and needs of a customer. Knowledge-based recommender applications meet these requirements by allowing the calculation of personalized solutions based on an explicit representation of(More)
Debugging of ontologies is an important prerequisite for their widespread application, especially in areas that rely upon everyday users to create and maintain knowledge bases, as in the case of the Semantic Web. Recent approaches use diagnosis methods to identify causes of inconsistent or incoherent ontologies. However, in most debugging scenarios these(More)
Customers interacting with online selling platforms require the assistance of sales support systems in the product and service selection process. Knowledge-based recommenders are specific sales support systems which involve online customers in dialogs with the goal to support preference forming processes. These systems have been successfully deployed in(More)
The process of instantiating an ontology with high-quality and up-to-date instance information manually is both time consuming and prone to error. Automatic ontology instantiation from Web sources is one of the possible solutions to this problem and aims at the computer supported population of an ontol-ogy through the exploitation of (redundant) information(More)
The process of populating an ontology-based system with high-quality and up-to-date instance information can be both time consuming and prone to error. In many domains, however, one possible solution to this problem is to automate the instantiation process for a given ontology by searching (mining) the web for the required instance information. The primary(More)
Web Mining Systems exploit the redundancy of data published on the Web to automatically extract information from existing web documents. The first step in the Information Extraction process is thus to locate as many web pages as possible that contain relevant information within a limited period of time, a task which is commonly accomplished by applying(More)
The computation of minimal conflict sets is a central task when the goal is to find relaxations or explanations for overconstrained problem formulations and in particular in the context of Model-Based Diagnosis (MBD) approaches. In this paper we propose MERGEXPLAIN, a non-intrusive conflict detection algorithm which implements a divide-and-conquer strategy(More)