IRQAS: information retrieval and question answering system based on a unified logical-linguistic model
Tengku Mohd Tengku Sembok, Halimah Badioze Zaman, Rabiah Abdul Kadir · International Conference on Artificial Intelligence · 2008
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.