Grant: Canada Research Chairs

The term ""Google"" has become a verb for most of us. Search engines, however, have certain limitations. For example ask it for the impact of the current global financial crisis in different parts of the world, and you can expect to sift through thousands of results for the answer. This motivates the research in complex question answering where the purpose is to create summaries of large volumes of information as answers to complex questions, rather than simply offering a listing of sources. Unlike simple questions, complex questions cannot be answered easily as they often require inferencing and synthesizing information from multiple documents. Inferencing and synthesizing information from multiple documents require extracting, organizing, and inter-relating the pieces of information contained in a set of relevant documents, in order to obtain a comprehensive, non redundant report that satisfies the information need. Answering complex questions can be seen as a topic-oriented, informative multi-document summarization where the goal is to produce a single text as a compressed version of a set of documents with a minimum loss of relevant information. This research proposal deals with ways in which text summarization and question answering technologies can be combined to form truly useful information delivery tools. More precisely, the problems that we are planning to investigate are: developing text summarization and question answering models that answer complex questions, building decomposition models that decompose complex questions into simple questions easy to answer, constructing models that generate questions automatically, capturing users' needs and tailoring the answers as summaries to user needs, and designing intelligent mechanisms to process natural language (i.e., inference, synthesize and summarize information) as well as mechanisms for coherent and tailored information delivery. I am planning to develop models, technologies and tools to deliver to users information that is relevant and appropriate for the users receiving it, information that they can easily assimilate to enable them to perform their tasks, usually enabling better and more efficient decision-making.