Feiyu Xu | German Research Center for Artificial Intelligence (original) (raw)

Papers by Feiyu Xu

Information, 2019

Human agents in technical customer support provide users with instructional answers to solve a ta... more Human agents in technical customer support provide users with instructional answers to solve a task that would otherwise require a lot of time, money, energy, physical costs. Developing a dialogue system in this domain is challenging due to the broad variety of user questions. Moreover, user questions are noisy (for example, spelling mistakes), redundant and have various natural language expressions. In this work, we introduce a conversational system, MOLI (the name of our dialogue system), to solve customer questions by providing instructional answers from a knowledge base. Our approach combines models for question type and intent category classification with slot filling and a back-end knowledge base for filtering and ranking answers, and uses a dialog framework to actively query the user for missing information. For answer-ranking we find that sequential matching networks and neural multi-perspective sentence similarity networks clearly outperform baseline models, achieving a 43%...

International Conference on Agents and Artificial Intelligence (ICAART), 2015

A new method is proposed and evaluated that improves distantly supervised learning of pattern rul... more A new method is proposed and evaluated that improves distantly supervised learning of pattern rules for n-ary relation extraction. The new method employs knowledge from a large lexical semantic repository to guide the discovery of patterns in parsed relation mentions. It extends the induced rules to semantically relevant material outside the minimal subtree containing the shortest paths connecting the relation entities and also discards rules without any explicit semantic content. It significantly raises both recall and precision with roughly 20% f-measure boost in comparison to the baseline system which does not consider the lexical semantic information.

International Conference on Computational Linguistics (COLING), Posters Volume, 2010

This paper presents a new approach to improving relation extraction based on minimally supervised... more This paper presents a new approach to improving relation extraction based on minimally supervised learning. By adding some limited closed-world knowledge for confidence estimation of learned rules to the usual seed data, the precision of relation extraction can be considerably improved. Starting from an existing base-line system we demonstrate that utilizing limited closed world knowledge can effectively eliminate " dangerous " or plainly wrong rules during the bootstrapping process. The new method improves the reliability of the confidence estimation and the precision value of the extracted instances. Although recall suffers to a certain degree depending on the domain and the selected settings, the overall performance measured by F-score considerably improves. Finally we validate the adaptability of the best ranking method to a new domain and obtain promising results.

Workshop on Natural Language Processing Techniques for Educational Applications at the Annual Meeting of the Association for Computational Linguistics (NLP-TEA @ ACL), 2015

We propose a strategy for the semi-automatic generation of learning material for reading-comprehe... more We propose a strategy for the semi-automatic generation of learning material for reading-comprehension tests, guided by semantic relations embedded in expos-itory texts. Our approach combines methods from the areas of information extraction and paraphrasing in order to present a language teacher with a set of candidate multiple-choice questions and answers that can be used for verifying a language learners reading capabilities. We implemented a web-based prototype showing the feasibility of our approach and carried out a pilot user evaluation that resulted in encouraging feedback but also pointed out aspects of the strategy and prototype implementation which need improvements.

International Conference on Language Resources and Evaluation (LREC), 2016

Recent research shows the importance of linking linguistic knowledge resources for the creation o... more Recent research shows the importance of linking linguistic knowledge resources for the creation of large-scale linguistic data. We describe our approach for combining two English resources, FrameNet and sar-graphs, and illustrate the benefits of the linked data in a relation extraction setting. While FrameNet consists of schematic representations of situations, linked to lexemes and their valency patterns, sar-graphs are knowledge resources that connect semantic relations from factual knowledge graphs to the linguistic phrases used to express instances of these relations. We analyze the conceptual similarities and differences of both resources and propose to link sar-graphs and FrameNet on the levels of relations/frames as well as phrases. The former alignment involves a manual ontology mapping step, which allows us to extend sar-graphs with new phrase patterns from FrameNet. The phrase-level linking, on the other hand, is fully automatic. We investigate the quality of the automatically constructed links and identify two main classes of errors.

Proceedings of the …, 2002

... GOSSIP GALORE A Conversational Web Agent for Collecting and Sharing Pop Trivia. Download: htt... more ... GOSSIP GALORE A Conversational Web Agent for Collecting and Sharing Pop Trivia. Download: http://www.ofai.at/rascalli/publications/publicati CACHED: Download as a PDF. by Feiyu Xu , Peter Adolphs , Hans Uszkoreit , Xiwen Cheng , Hong Li. ...

The Compass2008 project is a sino-german cooperation, aiming at integrating advanced information ... more The Compass2008 project is a sino-german cooperation, aiming at integrating advanced information technologies to create a high-tech information system that helps visitors to access location-sensitive information services during the 2008 Olympic Games in their preferred language, offering a variety of service-adaptive modalities available on the mobile devices. In this paper, we demonstrate one of the COMPASS2008 services, the Smart Dining Service, to showcase the new interaction concepts between multimodality, multilingual and location-sensitive information search.

Proceedings of AAAI-05. …, 2005

Web Intelligence and Agent Systems: An International Journal, 2004

Abstract. We present a novel method for mining textual answers in Web pages using semi-structured... more Abstract. We present a novel method for mining textual answers in Web pages using semi-structured NL questions and Google for initial document retrieval. We exploit the redundancy on the Web by weighting all identified named entities (NEs) found in the relevant document set based ...

In this paper, we present a survey of challenges and solutions of multilingual and translingual i... more In this paper, we present a survey of challenges and solutions of multilingual and translingual information service systems. In contrast to the computational linguistics literature on such systems, we are approaching the theme here from an HCI perspective. We will argue for a strategy that reduces reliance on automatic free-text translation, language input and classical information retrieval while not giving up these less reliable technologies altogether. We will also opt for a close situation-driven integration of information and communication functionalities. The described solutions have been incorporated into a novel mobile combined information and communication system for foreign tourists that has been tested under realistic conditions by users from several countries. The system is developed by the German-Chinese cooperation project COMPASS2008, a research action within the Digital Olympics framework.