Ontologies and Adaptivity in Dialogue for Question Answering
Question answering (QA) has become one of the fastest growing topics in computational linguistics and information access. To advance research in the area of dialogue-based question answering, we propose a combination of methods from different scientific fields (i.e., Information Retrieval, Dialogue Systems, Semantic Web, and Machine Learning). This book sheds light on adaptable dialogue-based question answering. We demonstrate the technical and computational feasibility of the proposed ideas, the introspective methods in particular, by beginning with an extensive introduction to the dialogical problem domain which motivates the technical implementation. The ideas have been carried out in a mature natural language processing (NLP) system, the SmartWeb dialogue system, which was developed between 2004 and 2007 by partners from academia and industry. We have attempted to make this book a self-containing text and provide an extra section on the interdisciplinary scientific background. The target audience for this book comprises of researchers and students interested in the application potential of semantic technologies for difficult AI tasks such as working dialogue and QA systems.
What people are saying - Write a review
We haven't found any reviews in the usual places.
Part I Introduction and Scientific Background
Part II Ontologies and DialogueBased QA
Part III Introspection and Dialogue Adaptation
Other editions - View all
abox adaptable dialogue algorithms answer streams application architecture association rules automatic clarification classification complex components computational concepts confidence constraints context cross-validation data mining data set decision tree dialogue act dialogue management dialogue models dialogue processing dialogue reaction dialogue system dialogue-based question answering discourse ontology distribution domain emma evaluation example extraction feedback environment Figure filter focus framework function graph iHUB implemented input integration interac interaction interaction design patterns interpretation introspective mechanism item sets linguistic machine learning measures meta metacognition metadata mobile multimedia multimodal dialogue multimodal interaction natural language natural language processing ontology-based operationalisation optimisation output pattern language performance PMML predictive QA system reaction and presentation REAPR reinforcement learning relevant representation ROC curves scenario selection Semantic Mediator semantic web services server shows SmartWeb Sonntag specific speech recognition structures suitable target task tion transaction trigger types user feedback user interface values