SILOL: a simple logical-linguistic document retrieval system
Information Processing and Management: an International Journal - Special issue on natural language processing and information retrieval
Recent trends in automatic information retrieval
Proceedings of the 9th annual international ACM SIGIR conference on Research and development in information retrieval
Journal of the American Society for Information Science - Special topic issue on the history of documentation and information science: part II
Knowledge representation: logical, philosophical and computational foundations
Knowledge representation: logical, philosophical and computational foundations
Information Retrieval
Reading comprehension programs in a statistical-language-processing class
ANLP/NAACL-ReadingComp '00 Proceedings of the 2000 ANLP/NAACL Workshop on Reading comprehension tests as evaluation for computer-based language understanding sytems - Volume 6
A machine learning approach to answering questions for reading comprehension tests
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
Question Answering on the Semantic Web
IEEE Intelligent Systems
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Many existing search engines do not have an important capability, the capability to deduce an answer to a query based on information which reside in various parts of documents. The levels-of-processing theory proposes that there are many ways to process and code information and thus the knowledge representation used as surrogate to documents are qualitatively different. The capability of deduction is much depended on the knowledge representation framework used. We propose a unified logical-linguistic model as knowledge representation framework as a basis for indexing of documents as well as deduction capability to provide answers to queries. The approach applies semantic analysis in transforming and normalising information from natural language texts into a declarative knowledge based representation of first order predicate logic. Retrieval of relevant information can then be performed through plausible logical implication and answer to query is carried out using theorem proving technique. This paper elaborates on the model and how it is used in information retrieval and question answering system as one unified model.