@inproceedings{d3bfe03d3fea4b30bba560556ee4141e,
title = "Probabilistic model for definitional question answering",
abstract = "This paper proposes a probabilistic model for definitional question answering (QA) that reflects the characteristics of the definitional question. The intention of the definitional question is to request the definition about the question target. Therefore, an answer for the definitional question should contain the content relevant to the topic of the target, and have a representation form of the definition style. Modeling the problem of definitional QA from both the topic and definition viewpoints, the proposed probabilistic model converts the task of answering the definitional questions into that of estimating the three language models: topic language model, definition language model, and general language model. The proposed model systematically combines several evidences in a probabilistic framework. Experimental results show that a definitional QA system based on the proposed probabilistic model is comparable to state-of-the-art systems.",
keywords = "Definitional question answering, Language model, Probabilistic model",
author = "Han, {Kyoung Soo} and Song, {Young In} and Rim, {Hae Chang}",
year = "2006",
doi = "10.1145/1148170.1148210",
language = "English",
isbn = "1595933697",
series = "Proceedings of the Twenty-Ninth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval",
publisher = "Association for Computing Machinery (ACM)",
pages = "212--219",
booktitle = "Proceedings of the Twenty-Ninth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval",
address = "United States",
note = "29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval ; Conference date: 06-08-2006 Through 11-08-2006",
}