AI & Machine Learning with Meaningful Impact
My research connects the concepts and methods of social networks and the semantic web with machine learning and natural language processing. I am interested in combining human intelligence with artificial intelligence methodologies. I am specifically interested in methods that bridge the areas of connectionism and symbolic models applied to real-world applications
Ontology-based translation of natural language queries to SPARQL
Abstract: We present an implemented approach to transform natural language sentences into SPARQL, using background knowledge from ontologies and lexicons. Therefore, eligible technologies and data storage possibilities are analyzed and evaluated. The contributions of this paper are twofold. Firstly, we…
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…
AAAI 2014 Fall Symposium: Natural Language Access to Big Data (NLA2BD)
November 13–15, 2014. Westin Arlington Gateway in Arlington, Virginia adjacent to Washington, DC. Motivation and Scope: Today’s enterprises need to make decisions based on analyzing massive and heterogeneous data sources. More and more aspects of decision making are driven by…
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…
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…
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…
Knowledge Enhanced Embodied Cognitive Interaction Technology (KnowCIT)
CITEC – Cognitive Interaction Technology – Center of Excellence Summary The project has built a technology which enables artificial agents to explore “crowdsourced” knowledge resources generated by large communities of web users. Project: Knowledge Enhanced Embodied Cognitive Interaction Technology Supervisor(s): Ipke…
WikiQA – Question Answering
WikiQA is a German open domain question answering system that uses the Wikipedia as a knowledge base to answer natural language questions. It has been developed by the KnowCIT project (Artificial Intelligence Group) within the CITEC at Bielefeld University. Using…
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: KI – Künstliche Intelligenz, November 2012, Volume 26, Issue 4, pp 381-390 Abstract: Recent advances in Artificial Intelligence and Natural…
