Using webcrawling of publicly available websites to assess E-commerce relationships

We investigate e-commerce success factors concerning their impact on the success of commerce transactions between businesses companies. In scientific literature, many e-commerce success factors are introduced. Most of them are focused on companies' website quality. They are evaluated concerning companies' success in the business-to- consumer (B2C) environment where consumers choose their preferred e-commerce websites based on these success factors e.g. website content quality, website interaction, and website customization. In contrast to previous work, this research focuses on the usage of existing e-commerce success factors for predicting successfulness of business-to-business (B2B) ecommerce. The introduced methodology is based on the identification of semantic textual patterns representing success factors from the websites of B2B companies. The successfulness of the identified success factors in B2B ecommerce is evaluated by regression modeling. As a result, it is shown that some B2C e-commerce success factors also enable the predicting of B2B e-commerce success while others do not. This contributes to the existing literature concerning ecommerce success factors. Further, these findings are valuable for B2B e-commerce websites creation

Contextualized B2B Registries

Abstract. Service discovery is a fundamental concept underpinning the move towards dynamic service-oriented business partnerships. The business process for integrating service discovery and underlying registry technologies into business relationships, procurement and project management functions has not been examined and hence existing Web Service registries lack capabilities required by business today. In this paper we present a novel contextualized B2B registry that supports dynamic registration and discovery of resources within management contexts to ensure that the search space is constrained to the scope of authorized and legitimate resources only. We describe how the registry has been deployed in three case studies from important economic sectors (aerospace, automotive, pharmaceutical) showing how contextualized discovery can support distributed product development processes

Improving Schema Mapping by Exploiting Domain Knowledge

This dissertation addresses the problem of semi-automatically creating schema mappings. The need for developing schema mappings is a pervasive problem in many integration scenarios. Although the problem is well-known and a large body of work exists in the area, the development of schema mappings is today largely performed manually in industrial integration scenarios. In this thesis an approach for the semi-automatic creation of high quality schema mappings is developed

Semantic and Syntactic Matching of Heterogeneous e-Catalogues

In e-procurement, companies use e-catalogues to exchange product infor-mation with business partners. Matching e-catalogues with product requests helps the suppliers to identify the best business opportunities in B2B e-Marketplaces. But various ways to specify products and the large variety of e-catalogue formats used by different business actors makes it difficult. This Ph.D. thesis aims to discover potential syntactic and semantic rela-tionships among product data in procurement documents and exploit it to find similar e-catalogues. Using a Concept-based Vector Space Model, product data and its semantic interpretation is used to find the correlation of product data. In order to identify important terms in procurement documents, standard e-catalogues and e-tenders are used as a resource to train a Product Named Entity Recognizer to find B2B product mentions in e-catalogues. The proposed approach makes it possible to use the benefits of all availa-ble semantic resources and schemas but not to be dependent on any specific as-sumption. The solution can serve as a B2B product search system in e-Procurement platforms and e-Marketplaces

Modeling views in the layered view model for XML using UML

In data engineering, view formalisms are used to provide flexibility to users and user applications by allowing them to extract and elaborate data from the stored data sources. Conversely, since the introduction of Extensible Markup Language (XML), it is fast emerging as the dominant standard for storing, describing, and interchanging data among various web and heterogeneous data sources. In combination with XML Schema, XML provides rich facilities for defining and constraining user-defined data semantics and properties, a feature that is unique to XML. In this context, it is interesting to investigate traditional database features, such as view models and view design techniques for XML. However, traditional view formalisms are strongly coupled to the data language and its syntax, thus it proves to be a difficult task to support views in the case of semi-structured data models. Therefore, in this paper we propose a Layered View Model (LVM) for XML with conceptual and schemata extensions. Here our work is three-fold; first we propose an approach to separate the implementation and conceptual aspects of the views that provides a clear separation of concerns, thus, allowing analysis and design of views to be separated from their implementation. Secondly, we define representations to express and construct these views at the conceptual level. Thirdly, we define a view transformation methodology for XML views in the LVM, which carries out automated transformation to a view schema and a view query expression in an appropriate query language. Also, to validate and apply the LVM concepts, methods and transformations developed, we propose a view-driven application development framework with the flexibility to develop web and database applications for XML, at varying levels of abstraction