Determining off-topic questions in a question answering system using probabilistic language models

A computer system comprising:

• a processor(s) set;
• and a computer readable storage medium;
• wherein:
• the processor set is structured, located, connected and/or programmed to run program instructions stored on the computer readable storage medium;
• and
• the stored program instructions include:
• program instructions programmed to generate, for a question answering system adapted to answer questions for a particular domain, an on-topic probabilistic language model and an off-topic probabilistic language model, wherein the on-topic probabilistic language model is generated using training questions that have been identified as being on-topic with respect to the particular domain, and wherein the off-topic probabilistic language model is generated using training questions that have been identified as being off-topic with respect to the particular domain;
• program instructions programmed to determine, for a question input into the question answering system:
• (i) a first logarithm probability associated with the question under the on-topic probabilistic language model, and (ii) a second logarithm probability associated with the question under the off-topic probabilistic language model;
• program instructions programmed to model, using a sigmoid function, a difference between the first logarithm probability and the second logarithm probability;
• program instructions programmed to assign, based, at least in part, on the modelled difference, a topic score to the question;
• and
• program instructions programmed to determine, based, at least in part, on the topic score assigned to the question, whether the questions is off-topic with respect to the particular domain.