Interaction History Based Answer Formulation for Question Answering

  • Rivindu Perera
  • Parma Nand
Part of the Communications in Computer and Information Science book series (CCIS, volume 468)


With the rapid growth in information access methodologies, question answering has drawn considerable attention among others. Though question answering has emerged as an interesting new research domain, still it is vastly concentrated on question processing and answer extraction approaches. Latter steps like answer ranking, formulation and presentations are not treated in depth. Weakness we found in this arena is that answers that a particular user has acquired are not considered, when processing new questions. As a result, current systems are not capable of linking two questions such as “When is the Apple founded?” with a previously processed question “When is the Microsoft founded?” generating an answer in the form of “Apple is founded one year later Microsoft founded, in 1976”. In this paper we present an approach towards question answering to devise an answer based on the questions already processed by the system for a particular user which is termed as interaction history for the user. Our approach is a combination of question processing, relation extraction and knowledge representation with inference models. During the process we primarily focus on acquiring knowledge and building up a scalable user model to formulate future answers based on current answers that same user has processed. According to evaluation we carried out based on the TREC resources shows that proposed technology is promising and effective in question answering.


Question answering Answer formulation Interaction history Natural Language Processing 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Rivindu Perera
    • 1
  • Parma Nand
    • 1
  1. 1.School of Computer and Mathematical SciencesAuckland University of TechnologyAucklandNew Zealand

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