A Comparative Study of the Application of Different Learning Techniques to Natural Language Interfaces

In this paper we present first results from a comparative study. Its aim is to test the feasibility of different inductive learning techniques to perform the automatic acquisition of linguistic knowledge within a natural language database interface. In our interface architecture the machine learning module replaces an elaborate semantic analysis component. The learning module learns the correct mapping of a user's input to the corresponding database command based on a collection of past input data. We use an existing interface to a production planning and control system as evaluation and compare the results achieved by different instance-based and model-based learning algorithms.Comment: 10 pages, to appear CoNLL9

Natural language processing

Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems

Improving Knowledge Retrieval in Digital Libraries Applying Intelligent Techniques

Nowadays an enormous quantity of heterogeneous and distributed information is stored in the digital University. Exploring online collections to find knowledge relevant to a user’s interests is a challenging work. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to be shared and reused in an efficient way. In this work we propose a comprehensive approach for discovering E-learning objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. We have used Case Based-Reasoning methodology to develop a prototype for supporting efficient retrieval knowledge from online repositories. We suggest a conceptual architecture for a semantic search engine. OntoUS is a collaborative effort that proposes a new form of interaction between users and digital libraries, where the latter are adapted to users and their surroundings

A reflective characterisation of occasional user

This work revisits established user classifications and aims to characterise a historically unspecified user category, the Occasional User (OU). Three user categories, novice, intermediate and expert, have dominated the work of user interface (UI) designers, researchers and educators for decades. These categories were created to conceptualise user's needs, strategies and goals around the 80s. Since then, UI paradigm shifts, such as direct manipulation and touch, along with other advances in technology, gave new access to people with little computer knowledge. This fact produced a diversification of the existing user categories not observed in the literature review of traditional classification of users. The findings of this work include a new characterisation of the occasional user, distinguished by user's uncertainty of repetitive use of an interface and little knowledge about its functioning. In addition, the specification of the OU, together with principles and recommendations will help UI community to informatively design for users without requiring a prospective use and previous knowledge of the UI. The OU is an essential type of user to apply user-centred design approach to understand the interaction with technology as universal, accessible and transparent for the user, independently of accumulated experience and technological era that users live in

A graphical user interface for Boolean query specification

On-line information repositories commonly provide keyword search facilities via textual query languages based on Boolean logic. However, there is evidence to suggest that the syntactical demands of such languages can lead to user errors and adversely affect the time that it takes users to form queries. Users also face difficulties because of the conflict in semantics between AND and OR when used in Boolean logic and English language. We suggest that graphical query languages, in particular Venn-like diagrams, can alleviate the problems that users experience when forming Boolean expressions with textual languages. We describe Vquery, a Venn-diagram based user interface to the New Zealand Digital Library (NZDL). The design of Vquery has been partly motivated by analysis of NZDL usage. We found that few queries contain more than three terms, use of the intersection operator dominates and that query refinement is common. A study of the utility of Venn diagrams for query specification indicates that with little or no training users can interpret and form Venn-like diagrams which accurately correspond to Boolean expressions. The utility of Vquery is considered and directions for future work are proposed