AI/NLP technologies applied to spacecraft mission design

In this paper we propose the model of a prototypical NLP architecture of an information access system to support a team of experts in a scientific design task, in a shared and heterogeneous framework. Specifically, we believe AI/NLP can be helpful in several tasks, such as the extraction of implicit information needs enclosed in meeting minutes or other documents, analysis of explicit information needs expressed through Natural Language, processing and indexing of document collections, extraction of required information from documents, modeling of a common knowledge base, and, finally, identification of important concepts through the automatic extraction of terms. In particular, we envisioned this architecture in the specific and practical scenario of the Concurrent Design Facility (CDF) of the European Space Agency (ESA), in the framework of the SHUMI project (Support To HUman Machine Interaction) developed in collaboration with the ESA/ESTEC - ACT (Advanced Concept Team). © Springer-Verlag Berlin Heidelberg 2005

Agent to Agent Talk: “Nobody There?” Supporting Agents Linguistic Communication

World-Wide Web technologies and the vision of Semantic Web have pushed for adaptive SW applications to scale up information technologies to the Web, where information is organized following different underlying knowledge and/or presentation models. Interoperability among heterogeneous intelligent agents has become an important research topic in the context of distributed information systems. Communication among heterogeneous agents involves several dimensions. “Ontological commitment” on a shared knowledge model cannot be assumed as a default. To overcome this problem, we will describe in this article a communication model that bases on the use of natural language. We will argue on main topics involved in using natural language to achieve semantic agreement in agents communication. The model foresees a strong separation among terms and concepts, this difference being often undervalued in the literature, where terms play the ambiguous role of both concept labels and of communication lexicon. For agents communicating through the language, lexical information embodies instead the possibility to “express” the underlying conceptualizations thus agreeing to a shared representation. We will examine in details the different layers involved in agents communication and we will focus on a the different roles played by each element. A novel agent architecture able to tackle with possible linguistic ambiguities by focusing on the conversational level will be deeply described. Three different agent typologies will be presented: Resource agents, embodying the target knowledge, Service agents, providing basic skills to support complex activities and control agents, supplying the structural knowledge of the task, with coordination and control capabilities. NL communication is supported by two dedicated Service agents: a Mediator, that will handle conceptual mismatches arising during communication, and a Translator, dealing with lexical misalignments due to different languages/idioms

A comparison of genetic algorithms for optimizing linguistically informed IR in question answering

In this paper we compare four selection strategies in evolutionary optimization of information retrieval (IR) in a question answering setting. The IR index has been augmented by linguistic features to improve the retrieval performance of potential answer passages using queries generated from natural language questions. We use a genetic algorithm to optimize the selection of features and their weights when querying the IR database. With our experiments, we can show that the genetic algorithm applied is robust to strategy changes used for selecting individuals. All experiments yield query settings with improved retrieval performance when applied to unseen data. However, we can observe significant runtime differences when applying the various selection approaches which should be considered when choosing one of these approaches

Purchasing the Web: an Agent based E-retail System with Multilingual Knowledge

3nonenonePAZIENZA M.T; STELLATO A; M. VINDIGNIPAZIENZA M., T; Stellato, A; Vindigni, Michel

AI/NLP TECHNOLOGIES APPLIED TO SPACECRAFT MISSION DESIGN

In this paper we propose the model of a prototypical NLP architecture of an information access system to support a team of experts in a scientific design task, in a shared and heterogeneous framework. Specifically, we believe AI/NLP can be helpful in several tasks, such as the extraction of implicit information needs enclosed in meeting minutes or other documents, analysis of explicit information needs expressed through Natural Language, processing and indexing of document collections, extraction of required information from documents, modeling of a common knowledge base, and, finally, identification of important concepts through the automatic extraction of terms. In particular, we envisioned this architecture in the specific and practical scenario of the Concurrent Design Facility (CDF) of the European Space Agency (ESA), in the framework of the SHUMI project (Support To HUman Machine Interaction) developed in collaboration with the ESA/ESTEC - ACT (Advanced Concept Team)