142,503 research outputs found
Robust question answering
A Question Answering (QA) system should provide a short and precise answer to a question in natural language, by searching a large knowledge base consisting of natural language text. The sources of the
knowledge base are widely available, for written natural language text is a preferential form of human communication. The information ranges from the more traditional edited texts, for example encyclopaedias or newspaper articles, to text obtained by modern automatic processes, as automatic speech recognizers.
The work developed in the present thesis focuses on the Portuguese language and open domain question answering, meaning that neither the questions nor the texts are restricted to a specific area, and it aims to
address both types of written text. Since information retrieval is essential for a QA system, a careful analysis of the current state-of-the-art in information retrieval and question answering components was conducted.
A complete, efficient and robust question answering system is developed in this thesis, consisting of new modules for information retrieval and question answering, that is competitive with current QA systems. The
system was evaluated at the Portuguese monolingual task of QA@CLEF 2008 and achieved the 3rd place in 6 Portuguese participants and 5th place among the 21 participants of 11 languages.
The system was also tested in Question Answering over Speech Transcripts (QAST), but outside the official evaluation QAST of QA@CLEF, since Portuguese was not among the available languages for this task. For
that reason, an entire test environment consisting of a corpus of transcribed broadcast news and a matching question set was built in the scope of this work, so that experiments could be made. The system proved to
be robust in the presence of automatically transcribed data, with results in line with the best reported at QAST.info:eu-repo/semantics/publishedVersio
Mobile Phone Text Processing and Question-Answering
Mobile phone text messaging between mobile users and information services is a growing area of
Information Systems. Users may require the service to provide an answer to queries, or may, in wikistyle, want to contribute to the service by texting in some information within the service’s domain of discourse. Given the volume of such messaging it is essential to do the processing through an automated service. Further, in the case of repeated use of the service, the quality of such a response has the potential to benefit from a dynamic user profile that the service can build up from previous texts of the same user.
This project will investigate the potential for creating such intelligent mobile phone services and aims to produce a computational model to enable their efficient implementation. To make the project feasible, the scope of the automated service is considered to lie within a limited domain of, for example, information about entertainment within a specific town centre. The project will assume the existence of a model of objects within the domain of discourse, hence allowing the analysis of texts within the context of a user model and a domain model. Hence, the project will involve the subject areas of natural language processing, language engineering, machine learning, knowledge extraction, and ontological engineering
A Factoid Question Answering System for Vietnamese
In this paper, we describe the development of an end-to-end factoid question
answering system for the Vietnamese language. This system combines both
statistical models and ontology-based methods in a chain of processing modules
to provide high-quality mappings from natural language text to entities. We
present the challenges in the development of such an intelligent user interface
for an isolating language like Vietnamese and show that techniques developed
for inflectional languages cannot be applied "as is". Our question answering
system can answer a wide range of general knowledge questions with promising
accuracy on a test set.Comment: In the proceedings of the HQA'18 workshop, The Web Conference
Companion, Lyon, Franc
Recommended from our members
AQUA: an ontology driven question answering system
This paper describes AQUA our question answering over the Web. AQUA was designed to work over heterogeneous sources. This means that AQUA is equipped to work as closed domain and in addition to open-domain question answering. As a first instance, AQUA tries to answer a question using a Knowledge base. If a query cannot be satisfied over a knowledge base/database. Then, AQUA tries to find an answer on web pages (i.e. it uses as corpus the internet as resource). Our system uses NLP (Natural Language Processing), First order logic and Information Extraction technologies. AQUA has been tested using an ontology which describes academic life. Keywords Ontologies, Information Extraction, Machine Learnin
- …