Term-driven E-Commerce

Die Arbeit nimmt sich der textuellen Dimension des E-Commerce an. Grundlegende Hypothese ist die textuelle Gebundenheit von Information und Transaktion im Bereich des elektronischen Handels. Überall dort, wo Produkte und Dienstleistungen angeboten, nachgefragt, wahrgenommen und bewertet werden, kommen natürlichsprachige Ausdrücke zum Einsatz. Daraus resultiert ist zum einen, wie bedeutsam es ist, die Varianz textueller Beschreibungen im E-Commerce zu erfassen, zum anderen können die umfangreichen textuellen Ressourcen, die bei E-Commerce-Interaktionen anfallen, im Hinblick auf ein besseres Verständnis natürlicher Sprache herangezogen werden

Building Web Directories in Different Languages for Decision Support: A Semi-Automatic Approach

Web directories organize voluminous information into hierarchical structures, helping users to quickly locate relevant information and to support decision-making. The development of existing Web directories either relies on expert participation that may not be available or uses automatic approaches that lack precision. As more users access the Web in their native languages, better approaches to organizing and developing non-English Web directories are needed. In this paper, we have proposed a semi-automatic approach to building domain-specific Web directories in different languages by combining human precision and machine efficiency. Using the approach, we have built Web directories in the Spanish business (SBiz) and Arabic medical (AMed) domains. Experimental results show that the SBiz and AMed directories achieved significantly better recall, F value, and satisfaction rating than benchmark directories. These encouraging results show that the approach can be used to build high-quality Web directories to support decision-making

CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges

Retrieval Enhancements for Task-Based Web Search

The task-based view of web search implies that retrieval should take the user perspective into account. Going beyond merely retrieving the most relevant result set for the current query, the retrieval system should aim to surface results that are actually useful to the task that motivated the query. This dissertation explores how retrieval systems can better understand and support their users’ tasks from three main angles: First, we study and quantify search engine user behavior during complex writing tasks, and how task success and behavior are associated in such settings. Second, we investigate search engine queries formulated as questions, and explore patterns in a large query log that may help search engines to better support this increasingly prevalent interaction pattern. Third, we propose a novel approach to reranking the search result lists produced by web search engines, taking into account retrieval axioms that formally specify properties of a good ranking.Die Task-basierte Sicht auf Websuche impliziert, dass die Benutzerperspektive berücksichtigt werden sollte. Über das bloße Abrufen der relevantesten Ergebnismenge für die aktuelle Anfrage hinaus, sollten Suchmaschinen Ergebnisse liefern, die tatsächlich für die Aufgabe (Task) nützlich sind, die diese Anfrage motiviert hat. Diese Dissertation untersucht, wie Retrieval-Systeme die Aufgaben ihrer Benutzer besser verstehen und unterstützen können, und leistet Forschungsbeiträge unter drei Hauptaspekten: Erstens untersuchen und quantifizieren wir das Verhalten von Suchmaschinenbenutzern während komplexer Schreibaufgaben, und wie Aufgabenerfolg und Verhalten in solchen Situationen zusammenhängen. Zweitens untersuchen wir Suchmaschinenanfragen, die als Fragen formuliert sind, und untersuchen ein Suchmaschinenlog mit fast einer Milliarde solcher Anfragen auf Muster, die Suchmaschinen dabei helfen können, diesen zunehmend verbreiteten Anfragentyp besser zu unterstützen. Drittens schlagen wir einen neuen Ansatz vor, um die von Web-Suchmaschinen erstellten Suchergebnislisten neu zu sortieren, wobei Retrieval-Axiome berücksichtigt werden, die die Eigenschaften eines guten Rankings formal beschreiben

Collaborative recommendations with content-based filters for cultural activities via a scalable event distribution platform

Nowadays, most people have limited leisure time and the offer of (cultural) activities to spend this time is enormous. Consequently, picking the most appropriate events becomes increasingly difficult for end-users. This complexity of choice reinforces the necessity of filtering systems that assist users in finding and selecting relevant events. Whereas traditional filtering tools enable e.g. the use of keyword-based or filtered searches, innovative recommender systems draw on user ratings, preferences, and metadata describing the events. Existing collaborative recommendation techniques, developed for suggesting web-shop products or audio-visual content, have difficulties with sparse rating data and can not cope at all with event-specific restrictions like availability, time, and location. Moreover, aggregating, enriching, and distributing these events are additional requisites for an optimal communication channel. In this paper, we propose a highly-scalable event recommendation platform which considers event-specific characteristics. Personal suggestions are generated by an advanced collaborative filtering algorithm, which is more robust on sparse data by extending user profiles with presumable future consumptions. The events, which are described using an RDF/OWL representation of the EventsML-G2 standard, are categorized and enriched via smart indexing and open linked data sets. This metadata model enables additional content-based filters, which consider event-specific characteristics, on the recommendation list. The integration of these different functionalities is realized by a scalable and extendable bus architecture. Finally, focus group conversations were organized with external experts, cultural mediators, and potential end-users to evaluate the event distribution platform and investigate the possible added value of recommendations for cultural participation

Data linking for the Semantic Web

By specifying that published datasets must link to other existing datasets, the 4th linked data principle ensures a Web of data and not just a set of unconnected data islands. The authors propose in this paper the term data linking to name the problem of finding equivalent resources on the Web of linked data. In order to perform data linking, many techniques were developed, finding their roots in statistics, database, natural language processing and graph theory. The authors begin this paper by providing background information and terminological clarifications related to data linking. Then a comprehensive survey over the various techniques available for data linking is provided. These techniques are classified along the three criteria of granularity, type of evidence, and source of the evidence. Finally, the authors survey eleven recent tools performing data linking and we classify them according to the surveyed techniques