A Collaborative Approach to Describe the Domain Language through the Language Extended Lexicon

Software development is a succession of descriptions in different languages in which every description is based on a previous one. Since the requirements specification is one of the first descriptions, it is important to begin software development with requirements that are as correct and as complete as possible. Although some literature holds the belief that correctness and completeness are two attributes that requirements specifications must satisfy, we know that these attributes are very difficult to meet. However, we have to find ways to diminish the level of incompleteness and deal with the possible conflicts that do arise in the requirements context. Defining the domain language before specifying the requirements is a way of coping with these problems. Nowadays, software systems involve many stakeholders and it is hard to engage all of them to produce a domain language specification. We rely on collaboration to foster the involvement and cooperation of the stakeholders, thus they are able to explore the differences constructively and provide a common understanding of the domain language beyond their own limited views. In this paper, we propose a strategy to capture the domain language in a collaborative way using the Language Extended Lexicon and we show a validation of the proposed strategy.Laboratorio de Investigación y Formación en Informática Avanzad

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

Building a Generation Knowledge Source using Internet-Accessible Newswire

In this paper, we describe a method for automatic creation of a knowledge source for text generation using information extraction over the Internet. We present a prototype system called PROFILE which uses a client-server architecture to extract noun-phrase descriptions of entities such as people, places, and organizations. The system serves two purposes: as an information extraction tool, it allows users to search for textual descriptions of entities; as a utility to generate functional descriptions (FD), it is used in a functional-unification based generation system. We present an evaluation of the approach and its applications to natural language generation and summarization.Comment: 8 pages, uses eps

Web 2.0, language resources and standards to automatically build a multilingual named entity lexicon

This paper proposes to advance in the current state-of-the-art of automatic Language Resource (LR) building by taking into consideration three elements: (i) the knowledge available in existing LRs, (ii) the vast amount of information available from the collaborative paradigm that has emerged from the Web 2.0 and (iii) the use of standards to improve interoperability. We present a case study in which a set of LRs for different languages (WordNet for English and Spanish and Parole-Simple-Clips for Italian) are extended with Named Entities (NE) by exploiting Wikipedia and the aforementioned LRs. The practical result is a multilingual NE lexicon connected to these LRs and to two ontologies: SUMO and SIMPLE. Furthermore, the paper addresses an important problem which affects the Computational Linguistics area in the present, interoperability, by making use of the ISO LMF standard to encode this lexicon. The different steps of the procedure (mapping, disambiguation, extraction, NE identification and postprocessing) are comprehensively explained and evaluated. The resulting resource contains 974,567, 137,583 and 125,806 NEs for English, Spanish and Italian respectively. Finally, in order to check the usefulness of the constructed resource, we apply it into a state-of-the-art Question Answering system and evaluate its impact; the NE lexicon improves the system’s accuracy by 28.1%. Compared to previous approaches to build NE repositories, the current proposal represents a step forward in terms of automation, language independence, amount of NEs acquired and richness of the information represented

Neurocognitive Informatics Manifesto.

Informatics studies all aspects of the structure of natural and artificial information systems. Theoretical and abstract approaches to information have made great advances, but human information processing is still unmatched in many areas, including information management, representation and understanding. Neurocognitive informatics is a new, emerging field that should help to improve the matching of artificial and natural systems, and inspire better computational algorithms to solve problems that are still beyond the reach of machines. In this position paper examples of neurocognitive inspirations and promising directions in this area are given

Specification Cases: a lightweight approach based on Natural Language

Use Cases are one of the most used artifacts in software requirements specifications. Although there are a lot of templates that suggests how to describe Use Cases, as well as many quality inspection techniques, there are no many techniques to deal with the complexity and the effort to produce good quality Use Cases. On top of that, Use Cases are biased towards user interaction, leaving out important domain information. Thus, it is necessary to provide techniques to incrementally describe specifications that goes beyond user interaction but which can be derived from simpler artifacts in order to make the process organized and effective. This paper proposes an approach to begin with very simple sentences (kernel sentences), following with the LEL glossary and Scenarios, in order to describe Specification Cases. The approach relies on already defined kernel sentences and suggests three procedures to reorganize the knowledge captured in kernel sentences to describe the LEL, then Scenarios and finally Use Cases. This paper also reports a preliminary evaluation that supports the applicability and usability of the approach