Smart Data Access: Semantic Web Technologies for Energy Diagnostics
Abstract: In today‘s (big) data-intensive world, scalable technologies enabling the efficient management, storage and analysis of large data set are needed. However, the underlying logic of the emerging data-driven business is very different to the established understanding of the traditional…
LinkedHealthAnswers: Towards Linked Data-driven Question Answering for the Health Care Domain
Abstract: This paper presents Linked Health Answers, a natural language question answering systems that utilizes health data drawn from the Linked Data Cloud. The contributions of this paper are three-fold: Firstly, we review existing state-of-the-art NLP platforms and components, with a special…
Natural Language Access to Enterprise Data
Abstract:This paper describes USI Answers — a natural language question answering system for enterprise data. We report on the progress towards the goal of offering easy access to enterprise data to a large number of business users, most of whom…
USI Answers: Natural Language Question Answering Over (Semi-) Structured Industry Data
Abstract: The paper reports on the progress towards the goal of offering easy access to enterprise data to a large number of business users, most of whom are not familiar with the specific syntax or semantics of the underlying data…
Market Intelligence: Linked Data-driven Entity Resolution for Customer and Competitor Analysis
Abstract: In this paper, we present a linked data-driven method for named entity recognition and disambiguation which is applied within an industry customer and competitor analysis application. The proposed algorithm primarily targets the domain of geoparsing and geocoding, but it…
Connecting Question Answering and Conversational Agents: Contextualizing German Questions for Interactive Question Answering Systems
Abstract: Research results in the field of Question Answering (QA) have shown that the classification of natural language questions significantly contributes to the accuracy of the generated answers. In this paper we present an approach which extends the prevalent question…
Digital Fruits For Lunch: Feeding Embodied Conversational Agents With Wikipedia Knowledge
Title: Digital Fruits For Lunch: Feeding Embodied Conversational Agents With Wikipedia Knowledge Authors: Ulli Waltinger, Alexa Breuing, Ipke Wachsmuth Pub/Conf: Interdisciplinary College Abstract: Recent advances in Artificial Intelligence and Natural Language Processing have enhanced the vision of using embodied conversational…
Interfacing Virtual Agents With Collaborative Knowledge: Open Domain Question Answering Using Wikipedia-based Topic Models
Abstract: This paper is concerned with the use of conversational agents as an interaction paradigm for accessing open domain encyclopedic knowledge by means of Wikipedia. More precisely, we describe a dialog-based question answering system for German which utilizes Wikipedia-based topic…
Talking Topically to the Artificial Agent Max
Title: Talking Topically to the Artificial Agent Max Authors: Breuing A, Waltinger U, Wachsmuth I Pub/Conf: Postersession at the Interdisciplinary College. Sankt Augustin, Germany: 488. 2011 Abstract: How do we recognize a topic in dialog? How can we detect topic shifts?…
Social Semantics And Its Evaluation By Means of Closed Topic Models: An SVM-Classification Approach Using Semantic Feature Replacement By Topic Generalization
Title: Social Semantics And Its Evaluation By Means of Closed Topic Models: An SVM-Classification Approach Using Semantic Feature Replacement By Topic Generalization Authors: Ulli Waltinger, Alexander Mehler, and Rüdiger Gleim Pub/Conf: GSCL-Conference 2009 Abstract: Text categorization is a fundamental part in…
