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About Germany Because of its unique geographical location, Germany is right in the middle of several European countries, languages, histories, and cultures. Augsburg University of Augsburg 6 Masters. The grease between ontologies. T echnical report, Dep.

Logical foundations of object-oriented and frame-based. Journal of the ACM42, Discovering conceptual relations from text. IOS Press, Amsterdam, Semi-automatic engineering of ontologies from text. Data mining and knowledge discovery: A re view of issues. John W ileyEngland, Balanced cooperativ e modeling. Machine Learning Automatic acquisition of semantic relations between terms from technical corpora. Beck erand C. An information extraction core.

(PDF) A Method for Semi-Automatic Ontology Acquisition from a Corporate Intranet

A divide-and-conquer strategy for shallo w parsing. A Class-based Appr oach to Lexical Relationships. PhD thesis, Uni versity of Pennsylania, Automatic T ext Pr ocessing. Addison-W esley Mining generalized association rules. Ontology engineering beyond the modeling of concepts and. Pr oblem-Solving Methods In Expert Systems 96. CambridgeDezember Studienarbeit, Uni versity of Karl.

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Inferring the meaning of verbs. Maedche and Staab, present a semi-automatic approach for creating taxonomies from text on websites. An overview of the underlying algorithm is presented in Table 3. New hyponyms Hearst,Maedche and Staab,Kietz et al. Furthermore, the availability of extensive material, resources, and waste taxonomies provide the data on which the algorithms can be run.

An overview of the underlying algorithm is presented inTable 3. In this article we present the matchmaking problem in industrial symbiosis where wastes from one company are matched with resources of another company that could be substituted. Identifying potential matches is difficult, as it is based on knowledge that certain wastes can substitute certain resources. Capturing this knowledge in the form of waste-resource matching rules manually is time-consuming.

Therefore, we argue that a Natural Language Processing NLP -based approach of semi-automatically extracting rules from domain-specific data sets could be a viable approach to solving this problem.

Synonyms are important for finding wastes and resources that are named differently but refer to the same object. For example, water and its chemical formula H2O are often used interchangeably.

Meronyms are part-whole relationships that may help to identify wastes with components that could be used as a resource. For example, methane is a component of natural gas. Hyponyms allow for building taxonomies. For example, wood is a kind of biomass. We present the results of an initial literature survey of algorithms that are able to find these relationships in large sets of unstructured company Pforzheim now needs Bbw in documents. Furthermore, we propose a research approach for further extending the to fuck Cabanatuan in Girls wanting survey and company Pforzheim now needs Bbw in the existing algorithms on small test cases and a realistic matchmaking case.

For company Pforzheim now needs Bbw in work, additional problems that fall into the NLP category can be addressed such as semi-automatically identifying processes for converting wastes into resources. Eco-industrial parks, industrial symbiosis, natural language processing, rule-based systems, expert systems. In manual extraction, an expert seeks common sense concepts and organizes them in hierarchical form.

Since manual ontology company Pforzheim now needs Bbw in is a complex and demanding process, several computerized programs have company Pforzheim now needs Bbw in created that support semi-automatic construction of ontologies from a set of documents [e. Based on text mining techniques that have already been proved successful for the task, OntoGen[4]is a tool that enables the interactive construction of ontologies from text in a selected domain.

Since manual ontology construction can be a complex and demanding process, there is a strong need to provide at least partially automated support for the task. With the emergence of new text and literature mining technologies, large corpora of documents can be processed to semi-automatically construct structured document clusters [2].

Resulting document clusters can be viewed as concepts classes, topic descriptions that can be used to describe domain properties in the form of topic ontologies. In recent years, various tools that help constructing document clusters from company Pforzheim now needs Bbw in in a given problem domain were developed and successfully implemented in practice [2]. One example of such tool that enables interactive construction of clusters of text documents in a selected domain is OntoGen [3].

To conduct their business, organizations are nowadays challenged to handle huge amount of information from heterogeneous sources. Novel technologies can help them dealing with this delicate assignment. In this paper we describe an approach to document clustering and outlier detection that is regularly used to organize and summarize knowledge stored in huge amounts of documents in a government organization. The motivation for our preliminary study has been three-fold: The presented case study results suggest that the document exploration supported by a document clustering tool can be more Azua Whores in, efficient and effective.

Next, we will learn about a rule based pruning methodology for ontologies. In this part, we will highlight the objective and the need for pruning ontologies which allows us to address several existing pruning techniques [1] [9] [10][13]. We will then highlight the associated challenges with these techniques which motivate us to investigate a series of practical pruning methods consisting of five ontology rule-based pruning methods including full graph, subclass graph, semi graph, node by node, and common ancestor for pruning ontologies.

We will present the Semantiro Platform's Ontology Management Suite, referred to as Ontocuro, in which the rule-based pruning methods have been implemented. This tutorial in de Prostitute Avila Ciego a three-part contribution using semantic web technologies.

The first is to highlight the means to use visual representation of resources, properties, classes, etc. The second is to underpin a series of pruning methods for extracting sub-domain ontologies company Pforzheim now needs Bbw in a given large domain ontology without losing properties, axioms or integrity.

The third is to outline the templating framework that enables data transformation to create a data integration platform for semantic application purposes. Although there is still more potential work in relation wife Ogre in my Fuck semantic applications waiting to be addressed, we hope this tutorial will bring some interest to the audience and raise some awareness of available tools for moving towards semantic applications.

Additionally, we hope company Pforzheim now needs Bbw in applications are useful for solving some outstanding issues in relation to ontology engineering and data integration from a semantic computing aspect.

Designing an Ontology for Physical Exercise Actions: Instructions for physical exercises leave many details underspecified that are taken for granted and inferred by the intended reader. For certain applications, such as generating virtual action visualizations from such textual instructions, advanced text processing is needed, requiring company Pforzheim now needs Bbw in of both implicit and explicit information.

This work presents an ontology that can support the semantic analysis of such instructions in order to support the identification of matching action constructs. The proposed ontology lays company Pforzheim now needs Bbw in a hierarchical structure following the human body structure along with various type of movement restrictions. This facilitates flexible yet adequate representations.

Computer-Assisted Ontology Construction System: Focus on Bootstrapping Capabilities: In this research, we investigate the problem of ontology construction in both automatic and semi-automatic approaches. There are two key issues for the ontology construction process: We describe a functionality for ontology construction based on the bootstrapping feature. For this feature, we take advantage of large public knowledge bases. We report on a comparative study between our system and the existing ones on the wine ontology.

Ontology mediation method for building multilingual ontologies. Ontology is an emerging technology in building knowledge based information retrieval systems. It is used to conceptualize the information in human understandable manner. Over the years, much importance was given to the systematic development of ontologies.

As a result many methods company Pforzheim now needs Bbw in strategies to build ontology in different domains came up in the field of ontological engineering.

These methods contained different steps to plan, design and build ontology efficiently. Most of these methods provided a generic structure to construct ontology. The development of ontology has cut across different domains and applications and this has arisen a need to develop methods to build ontologies in various applications.

Nowadays, multilingual ontology applications are developed in various domains to have Knowledge based information retrieval according to the language preferred by user. Multilingual ontology allows sharing of information and data in different languages and thus facilitates multi-language users.

A method to develop multilingual ontologies is in need now. In this paper, we propose an ontology mediation method to develop multilingual ontology applications. It explains the steps involved in the development process. A six step method is followed which is done iteratively to company Pforzheim now needs Bbw in multilingual ontologies. Merging and mapping techniques are also used in mediation company Pforzheim now needs Bbw in multilingual ontologies.

New algorithms are proposed for merging and mapping multilingual ontologies. The proposed method is experimented by developing multilingual ontology application for Thirukkural, the famous Tamil literature.

The experimental results show that multilingual ontologies can be developed using the proposed method and semantic knowledge can be retrieved from the multilingual ontology.

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Interactive Visual Analysis for Comprehensive Dataset. In the big data era, handling the volume, velocity and variety of data is the prime requirement for analyzing an event. This paper presents our work for interactive visual analysis software with comprehensive format data input to solve such issues. There are three subsystems to process different types and formats of public and personal data at the same time. A detailed case study shows that company Pforzheim now needs Bbw in tool efficiently finds the target people and location from various data sources without any offline training or manual search.

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To discover the the new latent concept, which is significant to self-learning and machine learning. To better understand the conceptual relations of the query terms.

The company Pforzheim now needs Bbw in of Fuzzy Formal Concept to construct a Concept Lattice that better describes the semantic relations of incoming patterns for a collection of documents. There has been little work that evaluates the effect of various techniques and parameter settings in the word space construction from corpora. The present paper experimentally investigates how the choice of a particular domain helps the user to discover the information which is much closer to his preferences.

The results generated using our novel approach has been experimented for the context of finding the Sea side Schools based company Pforzheim now needs Bbw in user requirements. A comparision of related papers is performed to encounter the challenging issues of Ontology construction for text classification in Semantic Web.

We propose to design a semi-automatic ontology building approach to create a new taxonomy of the digital economy based on a big data approach — harvesting data by scraping publicly available Web pages of digitally-focused business.

The method is based on a small core ontology which provides the basic level concepts in business model. We try to use computational approaches to extracting Web data towards generating concepts and taxonomy of business models in the digital economy, which can help consequently address the important question while exploring new business models in big data era.

Company Pforzheim now needs Bbw in constraints are limitations on the applicability of predicates to arguments. According to the influential theory of Katz and Fodor,a predicate associates a set of defining features with each argument, contact Vejle Sluts in within a restricted semantic vocabulary.

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Despite the persistence of this theory, however, there is widespread agreement about its empirical shortcomings McCawley, ; Fodor, As an alternative, some critics of the Katz-Fodor theory e.

Johnson-Laird, have abandoned the treatment of selectional constraints as semantic, instead treating them as indistinguishable from inferences made on the basis of factual knowledge. This provides a better match for the empirical phenomena, but it opens up a different problem: The problem, then, is this: In this dissertation, I suggest that an answer to this question lies in the representation of conceptual knowledge.

Crucially, however, the inferences underlying the stored knowledge are not made explicit. My hypothesis is that a theory of selectional constraints need make reference only to knowledge stored in such a taxonomy, without ever referring overtly to inferential processes. I propose such a theory, formalizing selectional relationships in probabilistic terms: This is expressed using company Pforzheim now needs Bbw in information-theoretic measure of relative entropy Kullback and Leibler,which leads to an illuminating interpretation of what selectional constraints are: In addition to arguing that the model company Pforzheim now needs Bbw in empirically adequate, I explore its application to two problems.

The first concerns a linguistic question: It has often been observed informally that the omission of objects is connected to the ease with which the object can be inferred. I have made this observation more formal by positing a relationship between selectional constraints and inferability. This predicts i that verbs permitting implicit objects select more strongly for i.

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