A Survey of Interfaces to Data Base and Expert Systems.

The problem of natural language recognition has been studied by many researchers since the early 1960‘s. In particular, researchers are concerned with building interfaces to existing systems, such as data base and expert systems. Such interfaces focus on easing communications between the underlying systems and the user. In this paper we survey various interfaces to both expert and data base systems. Natural language interfaces to data base systems have been quite successful. In contrast, natural language interfaces for expert systems are still in the initial stages of design. One mode of communication between an expert system and a user is via a menu interface. Such an interface presents many limitations [Datskovsky 84] [Datskovsky 85]. A natural language interface to expert systems that would not only alleviate such limitations, but also be domain independent and easily transportable from one system to another is desirable. By studying natural language interfaces to data base systems as well as existing interfaces to expert systems, we hope to gain insights on requirements for expert system interfaces and existing natural language technology that may help us in building natural language interfaces to ex pen systems

The development of a prototype intelligent user interface subsystem for NASA's scientific database systems

The National Space Science Data Center (NSSDC) has initiated an Intelligent Data Management (IDM) research effort which has as one of its components the development of an Intelligent User Interface (IUI).The intent of the latter is to develop a friendly and intelligent user interface service that is based on expert systems and natural language processing technologies. The purpose is to support the large number of potential scientific and engineering users presently having need of space and land related research and technical data but who have little or no experience in query languages or understanding of the information content or architecture of the databases involved. This technical memorandum presents prototype Intelligent User Interface Subsystem (IUIS) using the Crustal Dynamics Project Database as a test bed for the implementation of the CRUDDES (Crustal Dynamics Expert System). The knowledge base has more than 200 rules and represents a single application view and the architectural view. Operational performance using CRUDDES has allowed nondatabase users to obtain useful information from the database previously accessible only to an expert database user or the database designer

GAIML: A New Language for Verbal and Graphical Interaction in Chatbots

Natural and intuitive interaction between users and complex systems is a crucial research topic in human-computer interaction. A major direction is the definition and implementation of systems with natural language understanding capabilities. The interaction in natural language is often performed by means of systems called chatbots. A chatbot is a conversational agent with a proper knowledge base able to interact with users. Chatbots appearance can be very sophisticated with 3D avatars and speech processing modules. However the interaction between the system and the user is only performed through textual areas for inputs and replies. An interaction able to add to natural language also graphical widgets could be more effective. On the other side, a graphical interaction involving also the natural language can increase the comfort of the user instead of using only graphical widgets. In many applications multi-modal communication must be preferred when the user and the system have a tight and complex interaction. Typical examples are cultural heritages applications (intelligent museum guides, picture browsing) or systems providing the user with integrated information taken from different and heterogenous sources as in the case of the iGoogle™ interface. We propose to mix the two modalities (verbal and graphical) to build systems with a reconfigurable interface, which is able to change with respect to the particular application context. The result of this proposal is the Graphical Artificial Intelligence Markup Language (GAIML) an extension of AIML allowing merging both interaction modalities. In this context a suitable chatbot system called Graphbot is presented to support this language. With this language is possible to define personalized interface patterns that are the most suitable ones in relation to the data types exchanged between the user and the system according to the context of the dialogue

Multimodal Interaction Recognition Mechanism by Using Midas Featured By Data-Level and Decision-Level Fusion

Natural User Interfaces (NUI's) dealing with gestures is an alternative of traditional input devices on multi-touch panels. Rate of growth in the Sensor technology has increased the use of multiple sensors to deal with various monitoring and compatibility issues of machines. Research on data-level fusion models requires more focus on the fusion of multiple degradation-based sensor data. Midas, a novel declarative language to express multimodal interaction patterns has come up with the idea of developers required patterns description by employing multi-model interaction mechanism. The language as a base interface deals with minimum complexity issues like controlling inversion and intermediary states by means of data fusion, data processing and data selection provisioning high-level programming abstractions

Customizing One's Own Interface Using English as Primary Language

ASK, A Simple Knowledgeable System, is a total system for the structuring manipulation and communication of information. Its primary user interface is a dialect of English. In this interface, the user may work with texts, pictures and images, a l l integrated within the same semantic net data base. We concentrate here on the ASK System facilities f o r customizing the user's interface which are at a series of levels, from those immediately available to the user to those best exercised by the applications programmer. The user can extend his vocabulary, not only by new terms -- names and attributes, nouns and verbs -- but also by definitions. ASK includes two dialogue systems that are of particular importance for customizing the user's environment. The Dialogue Designing Dialogue is a complete natural language automatic programming system. The user can create his own mini-expert systems, so he can accomplish complex tasks by means of a simple dialogue. With some knowledge of programming, recursive calls, stacks, etc. provide powerful tools, all at the high level of anatural language dialogue. The Foreign Access Dialogue can be used to establish lines of communication to other, foreign, data bases, so that in answer to a single query, the system integrates data from the user's own data base and foreign data bases. No restriction is placed on these heterogeneous data bases other than their accessibility, possibly over phone lines, to the ASK system computer. Corresponding to each natural language context for user interaction, there is a meta-context for the applications programmer.. The central notion of meta-contexts is the rule of grammar and associated interpretive procedure. The applications programmer adds new capabilities by adding such rules, thus extending the range of resources at the fingertips of the user

A Domain-Specific Language for Do-It-Yourself Analytical Mashups

The increasing amount and variety of data available in the web leads to new possibilities in end-user focused data analysis. While the classic data base technologies for data integration and analysis (ETL and BI) are too complex for the needs of end users, newer technologies like web mashups are not optimal for data analysis. To make productive use of the data available on the web, end users need easy ways to find, join and visualize it. We propose a domain specific language (DSL) for querying a repository of heterogeneous web data. In contrast to query languages such as SQL, this DSL describes the visualization of the queried data in addition to the selection, filtering and aggregation of the data. The resulting data mashup can be made interactive by leaving parts of the query variable. We also describe an abstraction layer above this DSL that uses a recommendation-driven natural language interface to reduce the difficulty of creating queries in this DSL

A software based mentor system

This thesis describes the architecture, implementation issues and evaluation of Mentor - an educational support system designed to mentor students in their university studies. Students can ask (by typing) natural language questions and Mentor will use several educational paradigms to present information from its Knowledge Base or from data-mined online Web sites to respond. Typically the questions focus on the student’s assignments or in their preparation for their examinations. Mentor is also pro-active in that it prompts the student with questions such as "Have you started your assignment yet?". If the student responds and enters into a dialogue with Mentor, then, based upon the student’s questions and answers, it guides them through a Directed Learning Path planned by the lecturer, specific to that assessment. The objectives of the research were to determine if such a system could be designed, developed and applied in a large-scale, real-world environment and to determine if the resulting system was beneficial to students using it. The study was significant in that it provided an analysis of the design and implementation of the system as well as a detailed evaluation of its use. This research integrated the Computer Science disciplines of network communication, natural language parsing, user interface design and software agents, together with pedagogies from the Computer Aided Instruction and Intelligent Tutoring System fields of Education. Collectively, these disciplines provide the foundation for the two main thesis research areas of Dialogue Management and Tutorial Dialogue Systems. The development and analysis of the Mentor System required the design and implementation of an easy to use text based interface as well as a hyper- and multi-media graphical user interface, a client-server system, and a dialogue management system based on an extensible kernel. The multi-user Java-based client-server system used Perl-5 Regular Expression pattern matching for Natural Language Parsing along with a state-based Dialogue Manager and a Knowledge Base marked up using the XML-based Virtual Human Markup Language. The kernel was also used in other Dialogue Management applications such as with computer generated Talking Heads. The system also enabled a user to easily program their own knowledge into the Knowledge Base as well as to program new information retrieval or management tasks so that the system could grow with the user. The overall framework to integrate and manage the above components into a usable system employed suitable educational pedagogies that helped in the student’s learning process. The thesis outlines the learning paradigms used in, and summarises the evaluation of, three course-based Case Studies of university students’ perception of the system to see how effective and useful it was, and whether students benefited from using it. This thesis will demonstrate that Mentor met its objectives and was very successful in helping students with their university studies. As one participant indicated: ‘I couldn’t have done without it.

An authoring tool for decision support systems in context questions of ecological knowledge

Decision support systems (DSS) support business or organizational decision-making activities, which require the access to information that is internally stored in databases or data warehouses, and externally in the Web accessed by Information Retrieval (IR) or Question Answering (QA) systems. Graphical interfaces to query these sources of information ease to constrain dynamically query formulation based on user selections, but they present a lack of flexibility in query formulation, since the expressivity power is reduced to the user interface design. Natural language interfaces (NLI) are expected as the optimal solution. However, especially for non-expert users, a real natural communication is the most difficult to realize effectively. In this paper, we propose an NLI that improves the interaction between the user and the DSS by means of referencing previous questions or their answers (i.e. anaphora such as the pronoun reference in “What traits are affected by them?”), or by eliding parts of the question (i.e. ellipsis such as “And to glume colour?” after the question “Tell me the QTLs related to awn colour in wheat”). Moreover, in order to overcome one of the main problems of NLIs about the difficulty to adapt an NLI to a new domain, our proposal is based on ontologies that are obtained semi-automatically from a framework that allows the integration of internal and external, structured and unstructured information. Therefore, our proposal can interface with databases, data warehouses, QA and IR systems. Because of the high NL ambiguity of the resolution process, our proposal is presented as an authoring tool that helps the user to query efficiently in natural language. Finally, our proposal is tested on a DSS case scenario about Biotechnology and Agriculture, whose knowledge base is the CEREALAB database as internal structured data, and the Web (e.g. PubMed) as external unstructured information.This paper has been partially supported by the MESOLAP (TIN2010-14860), GEODAS-BI (TIN2012-37493-C03-03), LEGOLANGUAGE (TIN2012-31224) and DIIM2.0 (PROMETEOII/2014/001) projects from the Spanish Ministry of Education and Competitivity. Alejandro Maté is funded by the Generalitat Valenciana under an ACIF grant (ACIF/2010/298)

SWIP at QALD-3 : results, criticisms and lesson learned

International audienceThis paper presents the results obtained by the SWIP system while participating in the QALD-3 (Question Answering over Linked Data) challenge, co-located with CLEF 2013 (Conference and Labs of the Evaluation Forum). We tackled task 1, multilingual question answering, whose purpose is to interpret natural language questions in order to return the answers contained in a graph knowledge base. We answered queries of both proposed datasets (one concerning DBpedia, the other Musicbrainz) and took into consideration only questions in English. The system SWIP (Semantic Web Interface using Patterns) aims at automatically generating formal queries from user queries expressed in natural language. For this, it relies on the use of query patterns which enable the complex task of interpreting natural language queries. The results obtained on the Musicbrainz dataset (precision = 0,51, recall = 0,51, F-measure = 0,51) are very satisfactory and encouraging. The results on DBpedia (precision = 0,16, recall = 0,15, F-measure = 0,16) are more disappointing. In this paper, we present both the SWIP approach and its implementation. We then present the results of the challenge in more detail and their analysis. Finally we draw some conclusions on the strengths and weaknesses of our approach, and suggest ways to improve its performance